Configuring an application ingestion and replication task

1. 1Choose a runtime environment, if you haven't set up a default runtime environment.
2. 2Select a destination connection, or configure a new connection.
3. 3Select a source connection, or configure a new connection.
4. 4Specify task details for the source and target.
5. 5Configure trim transformations (optional).
6. 6Finalize the task definition by entering a task name, task definition location, runtime environment, and some optional properties. Then save the task..

Before you begin

• •Verify that the Secure Agent in your runtime environment is running and you can access the Data Ingestion and Replication service.
• •Define the source and target connections.

Starting the ingestion and replication task wizard

• •Click the Ingest panel. Then in the Ingestion and Replication Tasks dialog box, select Application Ingestion and Replication Task or Database Ingestion and Replication Task.
• •In the navigation bar on the left, click New. Then in the New Asset dialog box, click Data Ingestion and Replication and select either Application Ingestion and Replication Task or Database Ingestion and Replication Task.
If you previously selected a primary cloud data warehouse and use this method to start the wizard, the wizard does not recognize the primary cloud data warehouse as the destination. You'll need to select a destination for the task.

Primary cloud data warehouse setup

Configuring a primary cloud data warehouse

1On the Home page, click Yes, let's go in the Do you use a cloud data warehouse as your primary destination? panel.
2On the Destination page, select your cloud data warehouse type, for example, Snowflake Data Cloud or Databricks Delta, and click Next.
3On the Connect page, select a connection, or click New and enter the connection properties.
4Click Connect.

Changing or unselecting a primary cloud data warehouse

1On the Home page, click the cloud data warehouse type in the upper right corner and select Change primary cloud data warehouse.
2If you want to change your primary cloud data warehouse, select I have a primary cloud data warehouse.
3To change the cloud data warehouse type, complete the following steps:
1. aClick Change next to Type.
2. bOn the Destination page, select the data warehouse type, and then click Next.
3. cOn the Connect page, select a connection, or click New and enter the connection properties.
4. dClick Connect.
4To change the connection, complete the following steps:
1. aClick Change next to Connection.
2. bOn the Connect page, select a connection, or click New and enter the connection properties.
3. cClick Connect.
5If you no longer wish to use a primary cloud data warehouse, select I don’t have a primary cloud data warehouse, and click Save.

Choose a runtime environment

1In the Choose Runtime Environment dialog box, select the runtime environment you want to use.

Select Set as default if you want to use this runtime environment as the default environment for all tasks you create. Otherwise, leave the check box cleared.
2Click OK.
Note: When you finalize the task definition on the Let's Go page, you'll be prompted to enter the runtime environment for running the task. You can use this same runtime environment or select another one.

Configure the destination connection

• •To select an existing connection, select the box for the destination connection that you want to use. Then click Next.
• •To add a new connection, complete the following steps:
1. 1Click New Connection.
2. 2On the New Connection page > Destination tab, select the destination connection type. Then click Next.
3. 3On the Configure tab, enter the connection properties. To help you complete this task, the embedded Setup help on the right describes each property. To enlarge it, drag the left edge.
4. 4When done, click Test to check that the connection definition works.
5. 5Click Add to save it.
The new connection appears on the Destination page.
6. 6Select the box for the new connection and click Next.

Configure the source connection

• •To select an existing connection, select the box for the source connection that you want to use. Then click Next.
• •To add a new connection, complete the following steps:
1. 1Click New Connection.
2. 2In the New Connection dialog box > Source tab, select the source connection type. Then click Next.
3. 3On the Configure tab, enter the connection properties. To help you complete this task, the embedded setup help on the right describes each property. To enlarge it, drag the left edge.
4. 4Click Test to check that the connection definition works.
5. 5Click Add to save it.
The new connection appears on the Source page.
6. 6Select the box for the new connection and click Next.

Task details: Configure how to replicate data from the source

• •Configure an Adobe Analytics source
• •Configure a Google Analytics source
• •Configure a Marketo source
• •Configure a Microsoft Dynamics 365 source
• •Configure a NetSuite source
• •Configure an Oracle Fusion Cloud source
• •Configure a Salesforce source
• •Configure a Salesforce Marketing Cloud source
• •Configure an SAP source that uses the SAP OData V2 connector
• •Configure an SAP source that uses the SAP ODP Extractor connector
• •Configure an SAP source that uses the SAP Mass Ingestion connector
• •Configure a ServiceNow source
• •Configure a Workday source
• •Configure a Zendesk source

Configure an Adobe Analytics source

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
Path to Report Configuration File	The path to the JSON file that contains the report configurations.

2Under Source Objects, select the source objects from which you want to replicate data. Use one or both of the following methods:
• - On the Selected Objects tab, individually select the check box for each source object you want to include. Clear the check box for any objects you do not want to include. To select all objects, select the Object check box at the top.
The Field count for an object shows the total number of fields in the object.
If you select the objects you want to include, all the selected and unselected objects are displayed by default. To view the selected objects only, use the filter next to the object selection count and change the view from All to Selected.
To find objects or fields, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns objects and fields that include CDC anywhere in their names. To narrow the search to only object names or field names, select Object Name or Fields in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for objects.
To add an object rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing object rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an object rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the objects and fields that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the object names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an object name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple object rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if an object rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC objects.
You can both manually select source objects and define selection rules. If you first manually select objects on the Selected Objects tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any objects selected by those rules are displayed as selected on the Selected Objects tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Objects by Rule Type	Generate and download a list of the source objects that match the object selection criteria. If you used rule-based object selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Fields check box to include fields in the list, regardless of which object selection method you used. Click the Download icon to download the list.
Start Date	For initial load and combined initial and incremental load jobs, specify the date and time when the ingestion job should start replicating the source data. Note: The date and time must be in the time zone specified for ReportSuiteID in the JSON file with report configurations.
End Date	For initial load jobs, specify the date and time when the ingestion job should stop replicating the source data. Note: The date and time must be in the time zone specified for ReportSuiteID in the JSON file with report configurations.
Initial Start Point for Incremental Load	For incremental load jobs, specify the point in the source data stream from which the ingestion job associated with the application ingestion and replication task starts extracting change records. Note: You must specify the date and time in Coordinated Universal Time (UTC).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 1 day.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. The default value is 50000.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a Google Analytics source

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
Account ID	Enter the unique identifier of your Google Analytics service account.
Property ID	Enter the unique identifier of the property whose data you want to replicate.
View ID	Enter the unique identifier of the view whose data you want to replicate.
Path to Report Configuration File	The path to the JSON file that contains the report configurations.

2Under Source Reports, select the source reports that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Reports tab, individually select the check box for each source report you want to include. Clear the check box for any reports you do not want to include. To select all reports, select the Report check box at the top.
The Column count for a report shows the total number of columns in the report.
If you select the reports you want to include, all the selected and unselected reports are displayed by default. To view the selected reports only, use the filter next to the report selection count and change the view from All to Selected.
To find reports or columns, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns reports and columns that include CDC anywhere in their names. To narrow the search to only report names or column names, select Report Name or Columns in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for reports.
To add a report rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without the wildcards, as the condition.
Tips:
• ▪ You can copy an existing report rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit a report rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the reports and columns that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the reports to be included. For an Exclude rule, it shows the reports to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the report names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If a report name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple report rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if a report rule specifies "Exclude CDC" followed by "Include C", all reports with names beginning with "C" are selected, including the CDC report.
You can both manually select source reports and define selection rules. If you first manually select reports on the Selected Reports tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any reports selected by those rules are displayed as selected on the Selected Reports tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Reports by Rule Type	Generate and download a list of the source reports that match the report selection criteria. If you used rule-based report selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Columns check box to include columns in the list, regardless of which report selection method you used. Click the Download icon to download the list.
Start Date	For initial load and combined initial and incremental load jobs, specify the date and time when the ingestion job should start replicating the source data.
End Date	For initial load jobs, specify the date and time when the ingestion job should stop replicating the source data.
Initial Start Point for Incremental Load	For incremental load jobs, specify the point in the source data stream from which the ingestion job associated with the application ingestion and replication task starts extracting change records. Note: You must specify the date in the time zone configured for the Google Analytics view.
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 1 day.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. The default value is 50000.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a Marketo source

1Under Source Properties, configure the basic properties:

Property

Description

Load Type

Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.

2Under Source Objects, select the source objects from which you want to replicate data. Use one or both of the following methods:
• - On the Selected Objects tab, individually select the check box for each source object you want to include. Clear the check box for any objects you do not want to include. To select all objects, select the Object check box at the top.
The Field count for an object shows the total number of fields in the object.
If you select the objects you want to include, all the selected and unselected objects are displayed by default. To view the selected objects only, use the filter next to the object selection count and change the view from All to Selected.
To find objects or fields, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns objects and fields that include CDC anywhere in their names. To narrow the search to only object names or field names, select Object Name or Fields in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for objects.
To add an object rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing object rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an object rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the objects and fields that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the object names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an object name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple object rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if an object rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC objects.
You can both manually select source objects and define selection rules. If you first manually select objects on the Selected Objects tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any objects selected by those rules are displayed as selected on the Selected Objects tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Objects by Rule Type	Generate and download a list of the source objects that match the object selection criteria. If you used rule-based object selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Fields check box to include fields in the list, regardless of which object selection method you used. Click the Download icon to download the list.
Start Date	For initial load and combined initial and incremental load jobs, specify the date and time when the ingestion job should start replicating the source data.
Initial Start Poing for Incremental Load	For incremental load jobs, specify the point in the source data stream from which the ingestion job associated with the application ingestion and replication task starts extracting change records. Note: You must specify the date and time in Coordinated Universal Time (UTC).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a Microsoft Dynamics 365 source

1Under Source Properties, configure the basic properties:

Property

Description

Load Type

Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.

2Under Source Tables, select the source tables that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Tables tab, individually select the check box for each source table you want to include. Clear the check box for any tables you do not want to include. To select all tables, select the Table check box at the top.
The Column count for a table shows the total number of columns in the table.
If you select the tables you want to include, all the selected and unselected tables are displayed by default. To view the selected tables only, use the filter next to the table selection count and change the view from All to Selected.
To find tables or columns, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns tables and columns that include CDC anywhere in their names. To narrow the search to only table names or column names, select Table Name or Columns in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for tables.
To add a table rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing table rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit a table rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the tables and columns that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the table names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If a table name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple table rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if a table rule specifies "Exclude CDC" followed by "Include C", all tables with names beginning with "C" are selected, including the CDC tables.
You can both manually select source tables and define selection rules. If you first manually select tables on the Selected Tables tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any tables selected by those rules are displayed as selected on the Selected Tables tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Tables by Rule Type	Generate and download a list of the source tables that match the table selection criteria. If you used rule-based table selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Columns check box to include columns in the list, regardless of which table selection method you used. Click the Download icon to download the list.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: You must specify the date and time in Coordinated Universal Time (UTC).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a NetSuite source

1Under Source Properties, configure the basic properties:

Property

Description

Load Type

Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.

2Under Source Tables, select the tables and columns that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Tables tab, individually select the check box for each table and column you want to include. Clear the check box for any table and column you do not want to include. To select all tables and columns, select the Table check box at the top.
The Column count for a table shows the total number of columns in the table.
Note: If you deselect one or more columns for a table, a minus (-) appears next to the table name in the list.
If you select the tables you want to include, all the selected and unselected tables are displayed by default. To view the selected tables only, use the filter next to the table selection count and change the view from All to Selected.
To find tables or columns, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns tables and columns that include CDC anywhere in their names. To narrow the search to only table names or column names, select Table Name or Columns in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for tables and columns.
• ▪ To add a table rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without the wildcards, as the condition.
• ▪ To add a column rule for a table, click the plus (+) sign at the right end of the table row. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without the * wildcard, as the condition.
• ▪ Validate the rule. The validation warns if your rule excludes a primary key column.
Tips:
• ▪ You can copy an existing table rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit a table or column rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the tables and columns that match a rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the table and column names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If a table or column name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple table rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if a table rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC object.
You can both manually select tables and columns and define selection rules. If you first manually select tables and columns on the Selected Tables tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any tables and columns selected by those rules are displayed as selected on the Selected Tables tab. Expand the table on the Selection Rules tab to view details of the rules applied to fields.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Tables by Rule Type	Generate and download a list of the source tables that match the table selection criteria. If you used rule-based table selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Columns check box to include columns in the list, regardless of which table selection method you used. Click the Download icon to download the list.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: You must specify the date and time in Greenwich Mean Time (GMT).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. The default value is 5000.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure an Oracle Fusion Cloud source

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
Oracle Fusion Replication Approach	Select one of the following replication approaches - Select REST to extract data from various applications of Oracle Fusion such as ERP, SCM, HCM, Sales, and Services, and transfer data to the target. - Select BICC (Business Intelligence Cloud Connector) to extract bulk data from the source to the target.
Oracle Fusion Application	Select the application from which you want to replicate data.

2Under Source Objects, select the source objects from which you want to replicate data. Use one or both of the following methods:
• - On the Selected Objects tab, individually select the check box for each source object you want to include. Clear the check box for any objects you do not want to include. To select all objects, select the Object check box at the top.
The Field count for an object shows the total number of fields in the object.
If you select the objects you want to include, all the selected and unselected objects are displayed by default. To view the selected objects only, use the filter next to the object selection count and change the view from All to Selected.
To find objects or fields, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns objects and fields that include CDC anywhere in their names. To narrow the search to only object names or field names, select Object Name or Fields in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for objects.
To add an object rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing object rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an object rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the objects and fields that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the object names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an object name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple object rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if an object rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC objects.
You can both manually select source objects and define selection rules. If you first manually select objects on the Selected Objects tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any objects selected by those rules are displayed as selected on the Selected Objects tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Objects by Rule Type	Generate and download a list of the source objects that match the object selection criteria. If you used rule-based object selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Fields check box to include fields in the list, regardless of which object selection method you used. Click the Download icon to download the list.
Include Child Objects	Get the child object data of an object using an Oracle Fusion Cloud source. This applies only for the REST replication approach and for all load types only when the target is Google Big Query.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: You must specify the date and time in the time zone configured for the Oracle Fusion Cloud instance.
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. The default value is 50000.
Enable chunking	Select this checkbox to chunk data during the extraction process in an application ingestion and replication task. Chunking applies to initial load tasks, and in the initial portion in combined initial and incremental load tasks that use the BICC replication approach. Chunking is not applicable for CDC tasks. Options are: - None. Extracts data as a whole without dividing it into chunks. Default is None. - By Primary Key. Select this option to chunk data based on a numeric primay key. This option requires that your datastore contains a single numeric primary key column without Null values. - By Creation Date. Select this option to divide data into chunks at intervals defined by the number of days for date range extraction. This option requires selection of the Is Creation Date option in the BICC Console for a column or columns in the column list, which represent the creation date.
Number of Rows	If you select the By Primary Key chunking option, specify the number of rows to chunk extracts. Enter a positive integer. Make sure that the combination of total rows and chunk size results in no more than 250 chunks. For example, if you have 2500 rows with a chunk size of 10, it results in 250 chunks, which is the maximum chunks allowed.
Number of Days	If you select the By Creation Date chunking option, enter the number of days to set the interval for data extraction. For example, if you specify 365 days, the data is divided into segments that each cover a 365-day period, starting from the initial date. To prevent performance issues, consider specifying a larger number of days for the interval.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a Salesforce source

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
Salesforce API	For initial load tasks and combined initial and incremental load tasks, select the type of Salesforce API that you want to use to retrieve the source data. Options are: - Standard (REST) API: Replicates source fields of Base64 data type. Informatica recommends that you use the Bulk API 2.0 unless you want to ingest fields of Base64 data type or objects that are not supported by Bulk API 2.0 during initial loading of data. All incremental load activities use only the standard REST API. - Bulk API 2.0: Excludes replication of source fields of Base64 data type. Bulk API 2.0 is the default API for initial load tasks and the initial load of the combined initial and incremental load tasks. - Bulk API: Uses Bulk API 1.0 for primary-key chunking to achieve parallel processing in Salesforce that optimizes the performance and speed of initial and combined initial and incremental load jobs. Use this option to handle large-scale data from Salesforce. Note: By default, incremental load tasks can capture and replicate change data from source fields of Base64 data type.

2Under Source Objects, select the source objects and fields that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Objects tab, individually select the check box for each source object and field you want to include. Clear the check box for any objects and fields you do not want to include. To select all objects and fields, select the Object check box at the top.
The Field count for an object shows the total number of fields in the object.
Note: If you deselect one or more fields for an object, a minus (-) appears next to the object name in the list.
If you select the objects you want to include, all the selected and unselected objects are displayed by default. To view the selected objects only, use the filter next to the object selection count and change the view from All to Selected.
To find objects or fields, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns objects and fields that include CDC anywhere in their names. To narrow the search to only object names or field names, select Object Name or Fields in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for objects and fields.
• ▪ To add an object rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without the wildcards, as the condition.
• ▪ To add a field rule for an object, click the plus (+) sign at the right end of the object row. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without the * wildcard, as the condition.
• ▪ Validate the rule. The validation warns if your rule excludes a primary key field.
Tips:
• ▪ You can copy an existing object rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an object or field rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the objects and fields that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the object and field names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an object or field name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple object rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if an object rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC object.
You can both manually select source objects and fields and define selection rules. If you first manually select objects and fields on the Selected Objects tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any objects and fields selected by those rules are displayed as selected on the Selected Objects tab. Expand the object on the Selection Rules tab to view details of the rules applied to fields.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Objects by Rule Type	Generate and download a list of the source objects that match the object selection criteria. If you used rule-based object selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Fields check box to include fields in the list, regardless of which object selection method you used. Click the Download icon to download the list.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: You must specify the date and time in Greenwich Mean Time (GMT).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. The default value for initial load operations is 50000 and the default value for incremental load operations is 2000. Note: For combined initial and incremental load tasks, you must specify the fetch size separately for initial load operations and incremental load operations.
Include Base64 Fields	Select this check box to replicate the source fields of Base64 data type.
Maximum Base64 Body Size	If you selected the Include Base64 Fields check box, specify the maximum body size in megabytes (MB) for Base64 encoded data.
Include Archived and Deleted Rows	For initial load and combined initial and incremental load jobs, select this check box to replicate the archived and soft-deleted rows from the source during the initial loading of data.
Enable Partitioning	For initial load and combined initial and incremental load tasks, select this check box to partition the source objects for initial loading.
Chunk Size	If you enable partitioning of source objects,enter the number of records to be processed in a single partition. Based on the chunk size, bulk jobs are created in Salesforce. The default value is 50000 and the minimum value is 100.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Salesforce Max Parallel Partition	The maximum number of partition threads that can be used to query the source for data in parallel during initial load processing or the unload phase of combined jobs. Use this property to control the number of source partition queries that can be executed against the source at the same time. For example, if a table contains data in 100 partitions, all 100 partitions are queried at the same time by default. However, you can use this property to reduce the number of concurrent queries. Default value is equal to the total number of partitions.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a Salesforce Marketing Cloud source

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent.
MID	Enter the unique Member Identification code assigned to your Salesforce Marketing Cloud account.

2Under Source Objects, select the source objects from which you want to replicate data. Use one or both of the following methods:
• - On the Selected Objects tab, individually select the check box for each source object you want to include. Clear the check box for any objects you do not want to include. To select all objects, select the Object check box at the top.
The Field count for an object shows the total number of fields in the object.
If you select the objects you want to include, all the selected and unselected objects are displayed by default. To view the selected objects only, use the filter next to the object selection count and change the view from All to Selected.
To find objects or fields, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns objects and fields that include CDC anywhere in their names. To narrow the search to only object names or field names, select Object Name or Fields in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for objects.
To add an object rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing object rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an object rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the objects and fields that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the object names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an object name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple object rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if an object rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC objects.
You can both manually select source objects and define selection rules. If you first manually select objects on the Selected Objects tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any objects selected by those rules are displayed as selected on the Selected Objects tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Objects by Rule Type	Generate and download a list of the source objects that match the object selection criteria. If you used rule-based object selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Fields check box to include fields in the list, regardless of which object selection method you used. Click the Download icon to download the list.
Batch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. Default is 2500.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and then manuallly enter both the property name and value.
Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure an SAP source that uses the SAP OData V2 connector

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
OData Service Name	Select the OData service endpoint from where you want to retrieve data. The list contains a specific SAP service or a list of all available services on the SAP Gateway based on the service type you specified in the SAP OData V2 connection.

2Under Source Tables, select the source tables that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Tables tab, individually select the check box for each source table you want to include. Clear the check box for any tables you do not want to include. To select all tables, select the Table check box at the top.
The Column count for a table shows the total number of columns in the table.
If you select the tables you want to include, all the selected and unselected tables are displayed by default. To view the selected tables only, use the filter next to the table selection count and change the view from All to Selected.
To find tables or columns, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns tables and columns that include CDC anywhere in their names. To narrow the search to only table names or column names, select Table Name or Columns in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for tables.
To add a table rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing table rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit a table rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the tables and columns that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the table names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If a table name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple table rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if a table rule specifies "Exclude CDC" followed by "Include C", all tables with names beginning with "C" are selected, including the CDC tables.
You can both manually select source tables and define selection rules. If you first manually select tables on the Selected Tables tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any tables selected by those rules are displayed as selected on the Selected Tables tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Tables by Rule Type	Generate and download a list of the source tables that match the table selection criteria. If you used rule-based table selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Columns check box to include columns in the list, regardless of which table selection method you used. Click the Download icon to download the list.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs.
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 1 day.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure an SAP source that uses the SAP ODP Extractor connector

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
Context	Select the context containing the source data sources that you want to replicate on the target.

SAP ODP Extractor Connector supports the following ODP providers or contexts for all load types:

Providers/Context	Source SAP System and ODPs
SAP Service Application Programming Interface (S-API)	SAP Data Sources/Extractors without Enterprise Search (ESH)
HANA	SAP HANA Information View
BW	SAP NetWeaver Business Warehouse
ABAP_CDS	ABAP Core Data Services
SAP SLT	SLT Queue

2Under Source Data Sources, select the data sources that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Data Sources tab, individually select the check box for each data source you want to include. Clear the check box for any data sources you do not want to include. To select all data sources, select the Data Source check box at the top.
The Field count for a data source shows the total number of fields in the data source.
If you select the data sources you want to include, all the selected and unselected data sources are displayed by default. To view the selected data sources only, use the filter next to the data source selection count and change the view from All to Selected.
To find data sources or fields, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns data sources and fields that include CDC anywhere in their names. To narrow the search to only object names or field names, select Object Name or Fields in the drop-down list adjacent to the Find box.
• - Click Show Fields to display the actual columns from the SAP source. Otherwise, the columns for the selected data sources display as dummy.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for data sources.
To add a data source rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing object rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an object rule or field rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the objects and fields that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the data source names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an object name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple data source rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if a data source rule specifies "Exclude CDC" followed by "Include C", all data sources with names beginning with "C" are selected, including the CDC data source.
You can both manually select data sources and define selection rules. If you first manually select data sources on the Selected Data Sources tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any data sources selected by those rules are displayed as selected on the Selected Data Sources tab. Expand the source on the Selection Rules tab to view details of the rules applied to fields.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Data Sources by Rule Type	Generate and download a list of the data sources that match the table selection criteria. If you used rule-based table selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Fields check box to include fields in the list, regardless of which object selection method you used. Click the Download icon to download the list.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: By default, the ingestion job retrieves the change records from the latest available position in the data stream.
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes. Note: The CDC interval must be less than the data retention period configured in the SAP system for the Operational Delta Queue (ODQ).
Fetch Size	Enter the size of data that the application ingestion and replication job associated with the task reads at a time from the source. The value must be in megabytes (MB). The default value is 8.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure an SAP source that uses the SAP Mass Ingestion connector

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
Schema	For incremental load and combined initial and incremental load jobs, enter the underlying database schema that includes the source tables. Perform the following steps to enter the schema value: - Log in to the SAP application. - Browse to System > Status - Check the Owner value. Enter this value in the Schema field.

2Under Source Tables, select the tables and columns that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Tables tab, individually select the check box for each table and column you want to include. Clear the check box for any table and column you do not want to include. To select all tables and columns, select the Table check box at the top.
The Column count for a table shows the total number of columns in the table.
Note: If you deselect one or more columns for a table, a minus (-) appears next to the table name in the list.
If you select the tables you want to include, all the selected and unselected tables are displayed by default. To view the selected tables only, use the filter next to the table selection count and change the view from All to Selected.
To find tables or columns, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns tables and columns that include CDC anywhere in their names. To narrow the search to only table names or column names, select Table Name or Columns in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for tables and columns.
• ▪ To add a table rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without the wildcards, as the condition.
• ▪ To add a column rule for a table, click the plus (+) sign at the right end of the table row. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without the * wildcard, as the condition.
• ▪ Validate the rule. The validation warns if your rule excludes a primary key column.
Tips:
• ▪ You can copy an existing table rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit a table or column rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the tables and columns that match a rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the table and column names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If a table or column name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple table rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if a table rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC object.
You can both manually select tables and columns and define selection rules. If you first manually select tables and columns on the Selected Tables tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any tables and columns selected by those rules are displayed as selected on the Selected Tables tab. Expand the table on the Selection Rules tab to view details of the rules applied to fields.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
CDC Script	For incremental loads and combined initial and incremental loads, generate a script for enabling CDC on source tables and then run or download the script. The only available option is Enable CDC for all columns. Click Execute to run the script if you have the required privileges. Or click the Download icon to download the script so that you can give it to your DBA to run.
List Tables by Rule Type	Generate and download a list of the source tables that match the table selection criteria. If you used rule-based table selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Columns check box to include columns in the list, regardless of which table selection method you used. Click the Download icon to download the list.
Enable Persistent Storage	For incremental loads and combined initial and incremental loads, select this check box to enable persistent storage of transaction data in a disk buffer so that the data can be consumed continually, even when the writing of data to the target is slow or delayed. Benefits of using persistent storage are faster consumption of the source transaction logs, less reliance on log archives or backups, and the ability to still access the data persisted in disk storage after restarting an ingestion job. Persisted data is stored on the Secure Agent. It is not encrypted. The Secure Agent's files and directories are expected to be secured from unwanted access by using native file system access permissions or file system support of encryption natively.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: By default, the ingestion job retrieves the change records from the latest available position in the data stream.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a ServiceNow source

1Under Source Properties, configure the basic properties:

Property

Description

Load Type

Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.

2Under Source Tables, select the source tables that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Tables tab, individually select the check box for each source table you want to include. Clear the check box for any tables you do not want to include. To select all tables, select the Table check box at the top.
The Column count for a table shows the total number of columns in the table.
If you select the tables you want to include, all the selected and unselected tables are displayed by default. To view the selected tables only, use the filter next to the table selection count and change the view from All to Selected.
To find tables or columns, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns tables and columns that include CDC anywhere in their names. To narrow the search to only table names or column names, select Table Name or Columns in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for tables.
To add a table rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing table rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit a table rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the tables and columns that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the table names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If a table name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple table rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if a table rule specifies "Exclude CDC" followed by "Include C", all tables with names beginning with "C" are selected, including the CDC tables.
You can both manually select source tables and define selection rules. If you first manually select tables on the Selected Tables tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any tables selected by those rules are displayed as selected on the Selected Tables tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Tables by Rule Type	Generate and download a list of the source tables that match the table selection criteria. If you used rule-based table selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Columns check box to include columns in the list, regardless of which table selection method you used. Click the Download icon to download the list.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: You must specify the date and time in Greenwich Mean Time (GMT).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. The default value is 10000.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a Workday source

1Under Source Properties, configure the basic properties:

Property	Description
Load Type	Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.
Workday API	select the type of web service that you want to use to read source data. Options are: - SOAP: Uses SOAP APIs to extract Workday data. - RaaS: Uses Workday Report-as-a-Service (RaaS) to extract source data from custom objects and fields through custom reports. You can use Workday RaaS only in initial load jobs.

If you choose to use the SOAP API, perform the following steps:
1. aFrom the Product list, select Human Capital Management.
2. bFrom the Services list, select the Human Capital Management (HCM) services from which you want to ingest data to your target
You can select multiple services from the Services list.
3. cFrom the Output Type list, select the format in which you want the data to be stored on the target.
The ingestion jobs extract the source data in an XML structure. Based on the format that you select, the job writes the extracted data to the target as a single object in either JSON or XML format.
If you choose to use the RaaS API, perform the following steps:
1. aIn the Number of Reports field, select the number of reports you want to extract from the source.
2. bIf you choose to extract a single report, in the Report Name or URL field, enter the name or URL of the custom report you want to read from the source.
3. cIf you choose to extract multiple reports, in the Report Configuration File field, enter the path to the CSV file that you created for the list of custom reports that you want to read from the source.
2Under Source Operations, select the source operations that you want to replicate data from. Use one or both of the following methods:
• - On the Selected Operations tab, individually select the check box for each source operation you want to include. Clear the check box for any ooperations you do not want to include. To select all operations, select the Operation check box at the top.
The Attribute count for an operation shows the total number of attributes in the operation.
If you select the operations you want to include, all the selected and unselected operations are displayed by default. To view the selected operations only, use the filter next to the operation selection count and change the view from All to Selected.
To find operations or attributes, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns operations and attributes that include CDC anywhere in their names. To narrow the search to only operation names or field names, select Operation Name or Attributes in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for operations.
To add an operation rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing operation rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an operation rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the operations and attributes that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the source operation names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an source operation name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple operation rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if an operation rule specifies "Exclude CDC" followed by "Include C", all operations with names beginning with "C" are selected, including the CDC operations.
You can both manually select operations and define selection rules. If you first manually select operations on the Selected Operations tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any operations selected by those rules are displayed as selected on the Selected Operations tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Method	Description
List Operations by Rule Type	Generate and download a list of the sourceoperation that match the operation selection criteria. If you used rule-based operation selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Click the Download icon to download the list.
Initial Start Point for Incremental Load	For incremental load jobs, customize the position in the source logs from which the application ingestion and replication job starts reading change records the first time it runs. Note: You must specify the date and time in Coordinated Universal Time (UTC).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.
Fetch Size	Enter the number of records that the application ingestion and replication job associated with the task reads at a time from the source. The default value is 100. Note: The Fetch Size field appears only for the SOAP API.
Extract Non-default Fields	Select this check box to replicate the source fields that do not contain any default value. Note: The Extract Non-default Fields check box appears only for the SOAP API.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Configure a Zendesk source

1Under Source Properties, configure the basic properties:

Property

Description

Load Type

Type of load operation that you want the application ingestion and replication task to perform. You can select one of the following load types for the task: - Initial Load: Loads data read at a specific point in time from the source application to the target in a batch operation. You can perform an initial load to materialize a target to which incremental change data will be sent. - Incremental Load: Propagates source data changes to a target continuously or until the job is stopped or ends. The job propagates the changes that have occurred since the last time the job ran or from a specific start point for the first job run. - Initial and Incremental Load: Performs an initial load of point-in-time data to the target and then automatically switches to propagating incremental data changes made to the same source objects on a continuous basis.

2Under Source Objects, select the source objects from which you want to replicate data. Use one or both of the following methods:
• - On the Selected Objects tab, individually select the check box for each source object you want to include. Clear the check box for any objects you do not want to include. To select all objects, select the Object check box at the top.
The Field count for an object shows the total number of fields in the object.
If you select the objects you want to include, all the selected and unselected objects are displayed by default. To view the selected objects only, use the filter next to the object selection count and change the view from All to Selected.
To find objects or fields, you can type all or part of a name in the Find box and click Search. This value is case-sensitive. If you type the beginning of a name only, a wildcard isn't required to represent the remainder. For example, CDC, CD, and CD* return the same results. However, if the search string is within the name, include the wildcard * at the beginning. For example, *CDC returns objects and fields that include CDC anywhere in their names. To narrow the search to only object names or field names, select Object Name or Fields in the drop-down list adjacent to the Find box.
• - On the Selection Rules tab, you can create inclusion and exclusion rules for objects.
To add an object rule, click the plus (+) sign in the upper right corner. In the Type field, select Include or Exclude as the rule type. Then enter a string, with or without wildcards, as the condition.
Tips:
• ▪ You can copy an existing object rule to use as a starting point for creating another rule. Click the copy icon at the right end of the row.
• ▪ You can edit an object rule directly in its row by clicking the Type or Match Condition value.
• ▪ To view the objects and fields that match a single rule, click View Objects in the row for the rule. For an Include rule, it shows the objects to be included. For an Exclude rule, it shows the objects to be excluded.
When you define a condition in a rule, use the following guidelines:
• ▪ The task wizard is case sensitive. Enter the object names or masks in the case with which they were defined.
• ▪ A mask can contain one or more wildcards. Supported wildcards are: an asterisk (*), which represents one or more characters, and a question mark (?), which represents a single character. A wildcard can occur multiple times in a mask value and can occur anywhere in the value.
• ▪ Delimiters such as quotation marks or brackets are not allowed, even if the source uses them.
• ▪ If an object name includes special characters such as a backslash (\), asterisk(*), dollar sign ($), caret (^), or question mark (?), escape each special character with a backslash (\) when you enter the rule.
Note: If you define multiple object rules, they're processed in the order in which they're listed (top to bottom). Be sure to define them in the correct order of processing. For example, if an object rule specifies "Exclude CDC" followed by "Include C", all objects with names beginning with "C" are selected, including the CDC objects.
You can both manually select source objects and define selection rules. If you first manually select objects on the Selected Objects tab, rules are generated and displayed for those selections on the Selection Rules tab. Similarly, if you first define rules, any objects selected by those rules are displayed as selected on the Selected Objects tab.
3To configure advanced source properties, toggle on Show Advanced Options at the top of the page. Advanced source properties are optional or have default values. Complete the following optional advanced properties as needed:

Property	Description
List Objects by Rule Type	Generate and download a list of the source objects that match the object selection criteria. If you used rule-based object selection, you can select the type of selection rules to use. Options are: - Include Rules Only - Exclude Rules Only - Include And Exclude Rules Select the Include Fields check box to include fields in the list, regardless of which object selection method you used. Click the Download icon to download the list.
Initial Start Poing for Incremental Load	For incremental load jobs, specify the point in the source data stream from which the ingestion job associated with the application ingestion and replication task starts extracting change records. Note: You must specify the date and time in Coordinated Universal Time (UTC).
CDC Interval	For incremental load and combined initial and incremental load jobs, specify the time interval in which the application ingestion and replication job runs to retrieve the change records for incremental load. The default interval is 5 minutes.

4Under Custom Properties, you can specify one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available, depending on the load type:

Property	Description
Read Event Batch Size	The number of payload events written in batch to the internal event queue during CDC processing. When the event queue is implemented as an internal ring buffer, this value is the number of payload events that the reader writes to a single internal buffer slot. Note: A batch size that's too small might increase contention between threads. A larger batch size can provide for more parallelism but consume more memory.
Reader Helper Thread Count	The number of reader helper threads used during CDC processing to convert change data into a canonical format that can be passed to the target. Default value is 3. You can enter a larger value to allow more threads to be available for performing conversion processing in parallel.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed to Step 2 of Task Details.

Task details: Configure how to replicate data to the target

Under Target Properties, set the required basic target properties. Then toggle on Show Advanced Options at the top of the page to set optional advanced target properties as needed. See the property descriptions for your target type:
• - Configure an Amazon Redshift target
• - Configure an Amazon S3 target
• - Configure a Databricks target
• - Configure a Google BigQuery target
• - Configure a Google Cloud Storage target
• - Configure a Kafka target
• - Configure a Microsoft Azure Data Lake Storage Gen2 target
• - Configure a Microsoft Azure Synapse Analytics target
• - Configure a Microsoft Fabric OneLake target
• - Configure a Microsoft SQL Server target
• - Configure an Oracle Cloud Object Storage target
• - Configure an Oracle target
• - Configure a PostgreSQL target
• - Configure a Snowflake Cloud Data Warehouse target

Configure an Amazon Redshift target

1Under Target Properties, define the following target properties:

Property	Description
Target Creation	The only available option is Create Target Tables, which generates the target tables based on the source objects.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables.
Bucket	Specifies the name of the Amazon S3 bucket that stores, organizes, and controls access to the data objects that you load to Amazon Redshift.
Data Directory or Task Target Directory	Specifies the subdirectory where Application Ingestion and Replication stores output files for jobs associated with the task. This field is called Data Directory for an initial load job or Task Target Directory for an incremental load or combined initial and incremental load job.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Cycle ID	Select this check box to add a metadata column that includes the cycle ID of each CDC cycle in each target table. A cycle ID is a number that's generated by the CDC engine for each successful CDC cycle. If you integrate the job with Data Integration taskflows, the job can pass the minimum and maximum cycle IDs in output fields to the taskflow so that the taskflow can determine the range of cycles that contain new CDC data. This capability is useful if data from multiple cycles accumulates before the previous taskflow run completes. By default, this check box is not selected.
Prefix for Metadata Columns	Add a prefix to the names of the added metadata columns to easily identify them and to prevent conflicts with the names of existing columns. The default value is INFA_.
Enable Case Transformation	By default, target table names and column names are generated in the same case as the corresponding source names, unless cluster-level or session-level properties on the target override this case-sensitive behavior. If you want to control the case of letters in the target names, select this check box. Then select a Case Transformation Strategy option.
Case Transformation Strategy	If you selected Enable Case Transformation, select one of the following options to specify how to handle the case of letters in generated target table (or object) names and column (or field) names: - Same as source. Use the same case as the source table (or object) names and column (or field) names. - UPPERCASE. Use all uppercase. - lowercase. Use all lowercase. The default value is Same as source. Note: The selected strategy will override any cluster-level or session-level properties on the target for controlling case.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Configure an Amazon S3 target

1Under Target Properties, define the following required Amazon S3 target properties:

Property	Description
Open Table Format	The Open Table format to replicate data to Amazon S3. You can select from the following options: - Apache Iceberg. Replicates data to the Amazon S3 cloud storage as Apache Iceberg tables. You can access these tables directly from Amazon S3 using the AWS Glue Catalog. - None. Does not use an Open Table format to replicate data. The default value is None.
Namespace	The name of the database in AWS Glue Catalog where you want to store and manage your Apache Iceberg tables. This field appears only when you use an Open Table format.
Output Format	Select the format of the output file. Options are: - CSV - AVRO - PARQUET The default value is CSV if you do not use an Open Table format. If you select the Open table format, Parquet is selected by default for Apache Iceberg. Note: Output files in CSV format use double-quotation marks ("") as the delimiter for each field.
Warehouse Base Directory	The root directory in Amazon S3 to store the target files and tables when you use the Apache Iceberg Open Table format. This field appears only when you use an Open Table format.
Add Headers to CSV File	If CSV is selected as the output format, select this check box to add a header with source column names to the output CSV file.
Parquet Compression Type	If the PARQUET output format is selected, you can select a compression type that is supported by Parquet. Options are: - None - Gzip - Snappy The default value is None, which means no compression is used.
Avro Format	If you selected AVRO as the output format, select the format of the Avro schema that will be created for each source table. Options are: - Avro-Flat. This Avro schema format lists all Avro fields in one record. - Avro-Generic. This Avro schema format lists all columns from a source table in a single array of Avro fields. - Avro-Nested. This Avro schema format organizes each type of information in a separate record. The default value is Avro-Flat.
Avro Serialization Format	If AVRO is selected as the output format, select the serialization format of the Avro output file. Options are: - None - Binary - JSON The default value is Binary.
Avro Schema Directory	If AVRO is selected as the output format, specify the local directory where Application Ingestion and Replication stores Avro schema definitions for each source table. Schema definition files have the following naming pattern: schemaname_tablename.txt Note: If this directory is not specified, no Avro schema definition file is produced.
File Compression Type	Select a file compression type for output files in CSV or AVRO output format. Options are: - None - Deflate - Gzip - Snappy The default value is None, which means no compression is used.
Encryption Type	Select the encryption type for the Amazon S3 files when you write the files to the target. Options are: - None - Client Side Encryption - Client Side Encryption with KMS - Server Side Encryption - Server Side Encryption with KMS The default is None, which means no encryption is used.
Avro Compression Type	If AVRO is selected as the output format, select an Avro compression type. Options are: - None - Bzip2 - Deflate - Snappy The default value is None, which means no compression is used.
Deflate Compression Level	If Deflate is selected in the Avro Compression Type field, specify a compression level from 0 to 9. The default value is 0.
Add Directory Tags	For incremental load and combined initial and incremental load tasks, select this check box to add the "dt=" prefix to the names of apply cycle directories to be compatible with the naming convention for Hive partitioning. This check box is cleared by default.
Task Target Directory	For incremental load and combined initial and incremental load tasks, the root directory for the other directories that hold output data files, schema files, and CDC cycle contents and completed files. You can use it to specify a custom root directory for the task. If you enable the Connection Directory as Parent option, you can still optionally specify a task target directory to use with the parent directory specified in the connection properties. This field is required if the {TaskTargetDirectory} placeholder is specified in patterns for any of the following directory fields.
Data Directory	For initial load tasks, define a directory structure for the directories where Application Ingestion and Replication stores output data files and optionally stores the schema. The default directory pattern is {TableName)_{Timestamp}. To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter a folder name or use variables to create a folder name. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the initial load job starts to transfer data to the target. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: If you manually enter the directory expression, ensure that you enclose placeholders with curly brackets { }. Placeholder values are not case sensitive. For example: myDir1/{SchemaName}/{TableName} myDir1/myDir2/{SchemaName}/{YYYY}/{MM}/{TableName}_{Timestamp} myDir1/{toLower(SchemaName)}/{TableName}_{Timestamp} For incremental load and combined initial and incremental load tasks, define a custom path to the subdirectory that contains the cdc-data data files. The default directory pattern is {TaskTargetDirectory}/data/{TableName}/data To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter {TaskTargetDirectory} for a task-specific base directory on the target to use instead of the S3 folder path specified in the connection properties. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the CDC cycle started. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: For Amazon S3 and Microsoft Azure Data Lake Storage Gen2 targets, Application Ingestion and Replication uses the directory specified in the target connection properties as the root for the data directory path when Connection Directory as Parent is selected. For Google Cloud Storage targets, Application Ingestion and Replication uses the Bucket name that you specify in the target properties for the ingestion task. For Microsoft Fabric OneLake targets, the parent directory is the path specified in the Lakehouse Path field in the Microsoft Fabric OneLake connection properties. For Amazon S3 targets with Open Table format, the data directory field is not applicable. Enabling the Connection Directory as Parent includes the connection directory before the warehouse base path. If disabled, files are saved directly under the warehouse base directory.
Connection Directory as Parent	If you use the Open Table format, select this check box to use the directory value specified in the target connection properties as the parent directory. This path appends to the file path on S3 while creating the file. This check box is selected by default. For example, if the S3 directory set in the connection is myFolderOnS3/F1 and the Warehouse Base Directory is /myFold, files are saved to myFolderOnS3/F1/myFold/<files>. However, if you do not select the Connection Directory as Parent option, files are saved directly to /myFold/<files>. If you do not use the Open Table format, selecting this check box uses the directory value specified in the target connection properties as the parent directory for the custom directory paths specified in the task target properties. For initial load tasks, the parent directory is used in the Data Directory and Schema Directory. For incremental load and combined initial and incremental load tasks, the parent directory is used in the Data Directory, Schema Directory, Cycle Completion Directory, and Cycle Contents Directory. This check box is selected by default. If you clear it, for initial loads, define the full path to the output files in the Data Directory field. For incremental loads, optionally specify a root directory for the task in the Task Target Directory.
Schema Directory	Specify a custom directory in which to store the schema file if you want to store it in a directory other than the default directory. For initial loads, previously used values if available are shown in a list for your convenience. This field is optional. For initial loads, the schema is stored in the data directory by default. For incremental loads and combined initial and incremental loads, the default directory for the schema file is {TaskTargetDirectory}/data/{TableName}/schema You can use the same placeholders as for the Data Directory field. If you manually enter placeholders, ensure that you enclose them with curly brackets { }. If you include the toUpper or toLower function, put the placeholder name in parentheses and enclose both the function and placeholder in curly brackets, for example: {toLower(SchemaName)} Note: Schema is written only to output data files in CSV format. Data files in Parquet and Avro formats contain their own embedded schema.
Cycle Completion Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle completed file. Default is {TaskTargetDirectory}/cycle/completed.
Cycle Contents Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle contents files. Default is {TaskTargetDirectory}/cycle/contents.
Use Cycle Partitioning for Data Directory	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under each data directory. If this option is not selected, individual data files are written to the same directory without a timestamp, unless you define an alternative directory structure.
Use Cycle Partitioning for Summary Directories	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under the summary contents and completed subdirectories.
List Individual Files in Contents	For incremental load and combined initial and incremental load tasks, lists individual data files under the contents subdirectory. If Use Cycle Partitioning for Summary Directories is cleared, this option is selected by default. All of the individual files are listed in the contents subdirectory unless you can configure custom subdirectories by using the placeholders, such as for timestamp or date. If Use Cycle Partitioning for Data Directory is selected, you can still optionally select this check box to list individual files and group them by CDC cycle.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Operation Type	Select this check box to add a metadata column that records the source SQL operation type in the output that the job propagates to the target. For incremental loads, the job writes "I" for insert, "U" for update, or "D" for delete. For initial loads, the job always writes "I" for insert. By default, this check box is selected for incremental load and initial and incremental load jobs, and cleared for initial load jobs.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target. For initial loads, the job always writes the current date and time. By default, this check box is not selected.
Add Orderable Sequence	Select this check box to add a metadata column that records a combined epoch value and an incremental numeric value for each change operation that the job inserts into the target tables. The sequence value is always ascending, but not guaranteed to be sequential and gaps may exist. The sequence value is used to identify the order of activity in the target records. By default, this check box is not selected.
Add Before Images	Select this check box to include UNDO data in the output that a job writes to the target. For initial loads, the job writes nulls. By default, this check box is not selected.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed, or click Save.

Configure a Databricks target

1Under Target Properties, define the following required Databricks target properties:

Property	Description
Target Creation	The only available option is Create Target Tables, which generates the target tables based on the source objects.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables.
Apply Mode	For incremental load and combined initial and incremental load jobs, indicates how source DML changes, including inserts, updates, and deletes, are applied to the target. Options are: - Standard. Accumulate the changes in a single apply cycle and intelligently merge them into fewer SQL statements before applying them to the target. For example, if an update followed by a delete occurs on the source row, no row is applied to the target. If multiple updates occur on the same column or field, only the last update is applied to the target. If multiple updates occur on different columns or fields, the updates are merged into a single update record before being applied to the target. - Soft Deletes. Apply source delete operations to the target as soft deletes. A soft delete marks the deleted row as deleted without actually removing it from the database. For example, a delete on the source results in a change record on the target with "D" displayed in the INFA_OPERATION_TYPE column. After enabling Soft Deletes, any update in the source table during normal or backlog mode results in the deletion of the matching record, insertion of the updated record, and marking of the INFA_OPERATION_TYPE operation as NULL in the target table. Similarly, inserting a record in the source table during backlog mode results in marking the INFA_OPERATION_TYPE operation as E in the target table record. Consider using soft deletes if you have a long-running business process that needs the soft-deleted data to finish processing, to restore data after an accidental delete operation, or to track deleted values for audit purposes. - Audit. Apply an audit trail of every DML operation made on the source tables to the target. A row for each DML change on a source table is written to the generated target table along with the audit columns you select under the Advanced section. The audit columns contain metadata about the change, such as the DML operation type, transaction ID, and before image. Consider using Audit apply mode when you want to use the audit history to perform downstream computations or processing on the data before writing it to the target database or when you want to examine metadata about the captured changes. After enabling the Audit apply mode, any update in the source table during backlog or normal mode results in marking the INFA_OPERATION_TYPE operation as E in the target table record. Similarly, inserting a record in the source table during backlog mode results in marking the INFA_OPERATION_TYPE operation as E in the target table record. Default is Standard.
Data Directory or Task Target Directory	Specifies the subdirectory where Application Ingestion and Replication stores output files for jobs associated with the task. This field is called Data Directory for an initial load job or Task Target Directory for an incremental load or combined initial and incremental load job.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Operation Type	Select this check box to add a metadata column that records the source SQL operation type in the output that the job propagates to the target database or inserts into the target table. This field is available only when the Apply Mode option is set to Audit or Soft Deletes. In Audit mode, the job writes "I" for inserts, "U" for updates, "E" for upserts, or "D" for deletes to this metadata column. In Soft Deletes mode, the job writes "D" for deletes or NULL for inserts and updates. When the operation type is NULL, the other "Add Operation..." metadata columns are also NULL. Only when the operation type is "D" will the other metadata columns contain non-null values. By default, this check box is selected.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target. By default, this check box is not selected.
Add Operation Sequence	Select this check box to add a metadata column that records a generated, ascending sequence number for each change operation that the job inserts into the target tables. The sequence number reflects the change stream position of the operation. By default, this check box is not selected.
Add Before Images	Select this check box to include UNDO data in the output that a job writes to the target. By default, this check box is not selected.
Prefix for Metadata Columns	Add a prefix to the names of the added metadata columns to easily identify them and to prevent conflicts with the names of existing columns. The default value is INFA_.
Create Unmanaged Tables	Select this check box if you want the task to create Databricks target tables as unmanaged tables. After you deploy the task, you cannot edit this field to switch to managed tables. By default, this option is cleared and managed tables are created. If you selected Personal Staging Location in the Staging Environment field in the selected Databricks target connection, this check box is disabled. You cannot use unmanaged tables in this situation. For more information about Databricks managed and unmanaged tables, see the Databricks documentation.
Unmanaged Tables Parent Directory	If you choose to create Databricks unmanaged tables, you must specify a parent directory in Amazon S3 or Microsoft Azure Data Lake Storage to hold the Parquet files that are generated for each target table when captured DML records are processed. Note: To use Unity Catalog, you must provide an existing external directory. Note: For volume staging, provide the complete parent directory path.
Staging File Format	Select the format of the staging files in the staging environment specified in the Databricks connection. The files hold data before it's loaded into Databricks tables. Format options are: - CSV - Parquet Default is CSV.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can enter one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available for this target:

Property	Description
Writer Distributor Count	The number of distributors that can run on separate threads in parallel to process data during an initial load job or the unload phase of a combined load job when the Writer Unload Multiple Distributors custom property is set to true. Using parallel distributor threads can improve job performance, particularly for high-volume data transfers. Default value is 3. If your system has ample resources, Informatica recommends that you set this parameter to 8.
Writer Unload Multiple Distributors	Indicates whether multiple distributor threads can be used to process data in parallel during initial load jobs and the unload phase of combined load jobs. The distributors perform work such as uploading data files to staging areas and flushing data to the target. Set this property to true to use multiple distributor threads. Default value is false.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Configure a Google BigQuery target

1Under Target Properties, define the following required Google BigQuery target properties:

Property	Description
Target Creation	The only available option is Create Target Tables, which generates the target tables based on the source objects.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables.
Apply Mode	For incremental load and combined initial and incremental load jobs, indicates how source DML changes, including inserts, updates, and deletes, are applied to the target. Options are: - Standard. Accumulate the changes in a single apply cycle and intelligently merge them into fewer SQL statements before applying them to the target. For example, if an update followed by a delete occurs on the source row, no row is applied to the target. If multiple updates occur on the same column or field, only the last update is applied to the target. If multiple updates occur on different columns or fields, the updates are merged into a single update record before being applied to the target. - Audit. Apply an audit trail of every DML operation made on the source tables to the target. A row for each DML change on a source table is written to the generated target table along with the audit columns you select under the Advanced section. The audit columns contain metadata about the change, such as the DML operation type, time, owner, transaction ID, generated ascending sequence number, and before image. Consider using Audit apply mode when you want to use the audit history to perform downstream computations or processing on the data before writing it to the target database or when you want to examine metadata about the captured changes. - Soft Deletes. Apply source delete operations to the target as soft deletes. A soft delete marks the deleted row as deleted without actually removing it from the database. For example, a delete on the source results in a change record on the target with "D" displayed in the INFA_OPERATION_TYPE column. Consider using soft deletes if you have a long-running business process that needs the soft-deleted data to finish processing, to restore data after an accidental delete operation, or to track deleted values for audit purposes. Note: If you use Soft Deletes mode, you must not perform an update on the primary key in a source table. Otherwise, data corruption can occur on the target. The default value is Standard.
Bucket	Specifies the name of an existing bucket container that stores, organizes, and controls access to the data objects that you load to Google Cloud Storage.
Data Directory or Task Target Directory	Specifies the subdirectory where Application Ingestion and Replication stores output files for jobs associated with the task. This field is called Data Directory for an initial load job or Task Target Directory for an incremental load or combined initial and incremental load job.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Last Replicated Time	Select this check box to add a metadata column that records the timestamp at which a record was inserted or last updated in the target table. For initial loads, all loaded records have the same timestamp. For incremental and combined initial and incremental loads, the column records the timestamp of the last DML operation that was applied to the target. By default, this check box is not selected.
Add Operation Type	Select this check box to add a metadata column that records the source SQL operation type in the output that the job propagates to the target database or inserts into the audit table on the target system. This field is available only when the Apply Mode option is set to Audit or Soft Deletes. In Audit mode, the job writes "I" for inserts, "U" for updates, "E" for upserts, or "D" for deletes to this metadata column. In Soft Deletes mode, the job writes "D" for deletes or NULL for inserts, updates, and upserts. When the operation type is NULL, the other "Add Operation..." metadata columns are also NULL. Only when the operation type is "D" will the other metadata columns contain non-null values. By default, this check box is selected. You cannot deselect it if you are using soft deletes.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target tables. This field is available only when Apply Mode is set to Audit or Soft Deletes. By default, this check box is not selected.
Add Operation Sequence	Select this check box to add a metadata column that records a generated, ascending sequence number for each change operation that the job inserts into the target tables. The sequence number reflects the change stream position of the operation. This field is displayed only when the Apply Mode option is set to Audit. By default, this check box is not selected.
Add Before Images	Select this check box to add _OLD columns with UNDO "before image" data in the output that the job inserts into the target tables. You can then compare the old and current values for each data column. For a delete operation, the current value will be null. This field is displayed only when the Apply Mode option is set to Audit. By default, this check box is not selected.
Prefix for Metadata Columns	Add a prefix to the names of the added metadata columns to easily identify them and to prevent conflicts with the names of existing columns. Do not include special characters in the prefix. Otherwise, task deployment will fail. The default value is INFA_.
Enable Case Transformation	By default, target table names and column names are generated in the same case as the corresponding source names, unless cluster-level or session-level properties on the target override this case-sensitive behavior. If you want to control the case of letters in the target names, select this check box. Then select a Case Transformation Strategy option.
Case Transformation Strategy	If you selected Enable Case Transformation, select one of the following options to specify how to handle the case of letters in generated target table (or object) names and column (or field) names: - Same as source. Use the same case as the source table (or object) names and column (or field) names. - UPPERCASE. Use all uppercase. - lowercase. Use all lowercase. The default value is Same as source. Note: The selected strategy will override any cluster-level or session-level properties on the target for controlling case.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can enter one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available for this target:

Property	Description
Writer Distributor Count	The number of distributors that can run on separate threads in parallel to process data during an initial load job or the unload phase of a combined load job when the Writer Unload Multiple Distributors custom property is set to true. Using parallel distributor threads can improve job performance, particularly for high-volume data transfers. Default value is 3. If your system has ample resources, Informatica recommends that you set this parameter to 8.
Writer Unload Multiple Distributors	Indicates whether multiple distributor threads can be used to process data in parallel during initial load jobs and the unload phase of combined load jobs. The distributors perform work such as uploading data files to staging areas and flushing data to the target. Set this property to true to use multiple distributor threads. Default value is false.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Configure a Google Cloud Storage target

1Under Target Properties, define the following required Google Cloud Storage target properties:

Property	Description
Output Format	Select the format of the output file. Options are: - CSV - AVRO - PARQUET The default value is CSV if you do not use an Open Table format. If you select the Open table format, Parquet is selected by default for Apache Iceberg. Note: Output files in CSV format use double-quotation marks ("") as the delimiter for each field.
Add Headers to CSV File	If CSV is selected as the output format, select this check box to add a header with source column names to the output CSV file.
Parquet Compression Type	If the PARQUET output format is selected, you can select a compression type that is supported by Parquet. Options are: - None - Gzip - Snappy The default value is None, which means no compression is used.
Avro Format	If you selected AVRO as the output format, select the format of the Avro schema that will be created for each source table. Options are: - Avro-Flat. This Avro schema format lists all Avro fields in one record. - Avro-Generic. This Avro schema format lists all columns from a source table in a single array of Avro fields. - Avro-Nested. This Avro schema format organizes each type of information in a separate record. The default value is Avro-Flat.
Avro Serialization Format	If AVRO is selected as the output format, select the serialization format of the Avro output file. Options are: - None - Binary - JSON The default value is Binary.
Avro Schema Directory	If AVRO is selected as the output format, specify the local directory where Application Ingestion and Replication stores Avro schema definitions for each source table. Schema definition files have the following naming pattern: schemaname_tablename.txt Note: If this directory is not specified, no Avro schema definition file is produced.
File Compression Type	Select a file compression type for output files in CSV or AVRO output format. Options are: - None - Deflate - Gzip - Snappy The default value is None, which means no compression is used.
Avro Compression Type	If AVRO is selected as the output format, select an Avro compression type. Options are: - None - Bzip2 - Deflate - Snappy The default value is None, which means no compression is used.
Deflate Compression Level	If Deflate is selected in the Avro Compression Type field, specify a compression level from 0 to 9. The default value is 0.
Add Directory Tags	For incremental load and combined initial and incremental load tasks, select this check box to add the "dt=" prefix to the names of apply cycle directories to be compatible with the naming convention for Hive partitioning. This check box is cleared by default.
Bucket	Specifies the name of an existing bucket container that stores, organizes, and controls access to the data objects that you load to Google Cloud Storage.
Task Target Directory	For incremental load and combined initial and incremental load tasks, the root directory for the other directories that hold output data files, schema files, and CDC cycle contents and completed files. You can use it to specify a custom root directory for the task. If you enable the Connection Directory as Parent option, you can still optionally specify a task target directory to use with the parent directory specified in the connection properties. This field is required if the {TaskTargetDirectory} placeholder is specified in patterns for any of the following directory fields.
Data Directory	For initial load tasks, define a directory structure for the directories where Application Ingestion and Replication stores output data files and optionally stores the schema. The default directory pattern is {TableName)_{Timestamp}. To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter a folder name or use variables to create a folder name. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the initial load job starts to transfer data to the target. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: If you manually enter the directory expression, ensure that you enclose placeholders with curly brackets { }. Placeholder values are not case sensitive. For example: myDir1/{SchemaName}/{TableName} myDir1/myDir2/{SchemaName}/{YYYY}/{MM}/{TableName}_{Timestamp} myDir1/{toLower(SchemaName)}/{TableName}_{Timestamp} For incremental load and combined initial and incremental load tasks, define a custom path to the subdirectory that contains the cdc-data data files. The default directory pattern is {TaskTargetDirectory}/data/{TableName}/data To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter {TaskTargetDirectory} for a task-specific base directory on the target to use instead of the S3 folder path specified in the connection properties. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the CDC cycle started. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: For Amazon S3 and Microsoft Azure Data Lake Storage Gen2 targets, Application Ingestion and Replication uses the directory specified in the target connection properties as the root for the data directory path when Connection Directory as Parent is selected. For Google Cloud Storage targets, Application Ingestion and Replication uses the Bucket name that you specify in the target properties for the ingestion task. For Microsoft Fabric OneLake targets, the parent directory is the path specified in the Lakehouse Path field in the Microsoft Fabric OneLake connection properties. For Amazon S3 targets with Open Table format, the data directory field is not applicable. Enabling the Connection Directory as Parent includes the connection directory before the warehouse base path. If disabled, files are saved directly under the warehouse base directory.
Schema Directory	Specify a custom directory in which to store the schema file if you want to store it in a directory other than the default directory. For initial loads, previously used values if available are shown in a list for your convenience. This field is optional. For initial loads, the schema is stored in the data directory by default. For incremental loads and combined initial and incremental loads, the default directory for the schema file is {TaskTargetDirectory}/data/{TableName}/schema You can use the same placeholders as for the Data Directory field. If you manually enter placeholders, ensure that you enclose them with curly brackets { }. If you include the toUpper or toLower function, put the placeholder name in parentheses and enclose both the function and placeholder in curly brackets, for example: {toLower(SchemaName)} Note: Schema is written only to output data files in CSV format. Data files in Parquet and Avro formats contain their own embedded schema.
Cycle Completion Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle completed file. Default is {TaskTargetDirectory}/cycle/completed.
Cycle Contents Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle contents files. Default is {TaskTargetDirectory}/cycle/contents.
Use Cycle Partitioning for Data Directory	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under each data directory. If this option is not selected, individual data files are written to the same directory without a timestamp, unless you define an alternative directory structure.
Use Cycle Partitioning for Summary Directories	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under the summary contents and completed subdirectories.
List Individual Files in Contents	For incremental load and combined initial and incremental load tasks, lists individual data files under the contents subdirectory. If Use Cycle Partitioning for Summary Directories is cleared, this option is selected by default. All of the individual files are listed in the contents subdirectory unless you can configure custom subdirectories by using the placeholders, such as for timestamp or date. If Use Cycle Partitioning for Data Directory is selected, you can still optionally select this check box to list individual files and group them by CDC cycle.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Operation Type	Select this check box to add a metadata column that records the source SQL operation type in the output that the job propagates to the target. For incremental loads, the job writes "I" for insert, "U" for update, or "D" for delete. For initial loads, the job always writes "I" for insert. By default, this check box is selected for incremental load and initial and incremental load jobs, and cleared for initial load jobs.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target. For initial loads, the job always writes the current date and time. By default, this check box is not selected.
Add Orderable Sequence	Select this check box to add a metadata column that records a combined epoch value and an incremental numeric value for each change operation that the job inserts into the target tables. The sequence value is always ascending, but not guaranteed to be sequential and gaps may exist. The sequence value is used to identify the order of activity in the target records. By default, this check box is not selected.
Add Before Images	Select this check box to include UNDO data in the output that a job writes to the target. For initial loads, the job writes nulls. By default, this check box is not selected.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed, or click Save.

Configure a Kafka target

1Under Target Properties, define the following required Kafka target properties.
Note: These properties apply to incremental load operations only.

Property	Description
Use Table Name as Topic Name	Indicates whether Application Ingestion and Replication writes messages that contain source data to separate topics, one for each source object, or writes all messages to a single topic. Select this check box to write messages to separate table-specific topics. The topic names match the source table names, unless you add the source schema name, a prefix, or a suffix in the Include Schema Name, Table Prefix, or Table Suffix properties. By default, this check box is cleared.
Include Schema Name	When Use Table Name as Topic Name is selected, this check box appears and is selected by default. This setting adds the source schema name in the table-specific topic names. The topic names then have the format schemaname_tablename. If you do not want to include the schema name, clear this check box.
Table Prefix	When Use Table Name as Topic Name is selected, this property appears so that you can optionally enter a prefix to add to the table-specific topic names. For example, if you specify myprefix_, the topic names have the format myprefix_tablename. If you omit the underscore (_) after the prefix, the prefix is prepended to the table name.
Table Suffix	When Use Table Name as Topic Name is selected, this property appears so that you can optionally enter a suffix to add to the table-specific topic names. For example, if you specify _mysuffix, the topic names have the format tablename_mysuffix. If you omit the underscore (_) before the suffix, the suffix is appended to the table name.
Output Format	Select the format of the output file. Options are: - CSV - AVRO - JSON The default value is CSV. Note: Output files in CSV format use double-quotation marks ("") as the delimiter for each field. If your Kafka target uses Confluent Schema Registry to store schemas for incremental load jobs, you must select AVRO as the format.
JSON Format	If JSON is selected as the output format, select the level of detail of the output. Options are: - Concise. This format records only the most relevant data in the output, such as the operation type and the column names and values. - Verbose. This format records detailed information, such as the table name and column types.
Avro Format	If you selected AVRO as the output format, select the format of the Avro schema that will be created for each source table. Options are: - Avro-Flat. This Avro schema format lists all Avro fields in one record. - Avro-Generic. This Avro schema format lists all columns from a source table in a single array of Avro fields. - Avro-Nested. This Avro schema format organizes each type of information in a separate record. The default value is Avro-Flat.
Avro Serialization Format	If AVRO is selected as the output format, select the serialization format of the Avro output file. Options are: - Binary - JSON - None The default value is Binary. If you have a Confluent Kafka target that uses Confluent Schema Registry to store schemas, select None. Otherwise, Confluent Schema Registry does not register the schema. Do not select None if you are not using Confluent Scheme Registry.
Avro Schema Directory	If AVRO is selected as the output format, specify the local directory where Database Ingestion and Replication stores Avro schema definitions for each source table. Schema definition files have the following naming pattern: schemaname_tablename.txt Note: If this directory is not specified, no Avro schema definition file is produced. If a source schema change is expected to alter the target, the Avro schema definition file is regenerated with a unique name that includes a timestamp, in the following format: schemaname_tablename_YYYYMMDDhhmmss.txt This unique naming pattern ensures that older schema definition files are preserved for audit purposes.
Avro Compression Type	If AVRO is selected as the output format, select an Avro compression type. Options are: - None - Bzip2 - Deflate - Snappy The default value is None, which means no compression is used.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Operation Type	Select this check box to add a metadata column that includes the source SQL operation type in the output that the job propagates to the target. The job writes "I" for insert, "U" for update, or "D" for delete. By default, this check box is selected.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target. By default, this check box is not selected.
Add Orderable Sequence	Select this check box to add a metadata column that records a combined epoch value and an incremental numeric value for each change operation that the job inserts into the target tables. The sequence value is always ascending, but not guaranteed to be sequential and gaps may exist. The sequence value is used to identify the order of activity in the target records. By default, this check box is not selected.
Add Before Images	Select this check box to include UNDO data in the output that a job writes to the target. By default, this check box is not selected.
Async Write	Controls whether to use synchronous delivery of messages to Kafka. - Clear this check box to use synchronous delivery. Kafka must acknowledge each message as received before Application Ingestion and Replication sends the next message. In this mode, Kafka is unlikely to receive duplicate messages. However, performance might be slower. - Select this check box to use asynchronous delivery. Application Ingestion and Replication sends messages as soon as possible, without regard for the order in which the changes were retrieved from the source. By default, this check box is selected.
Producer Configuration Properties	Specify a comma-separated list of key=value pairs to enter Kafka producer properties for Apache Kafkatargets. You can specify Kafka producer properties in either this field or in the Additional Connection Properties field in the Kafka connection. If you enter the producer properties in this field, the properties pertain to the application ingestion and replication jobs associated with this task only. If you enter the producer properties for the connection, the properties pertain to jobs for all tasks that use the connection definition, unless you override the connection-level properties for specific tasks by also specifying properties in the Producer Configuration Properties field. For information about Kafka producer properties, see the Apache Kafka documentation.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed, or click Save.

Configure a Microsoft Azure Data Lake Storage Gen2 target

1Under Target Properties, define the following required Microsoft Azure Data Lake Storage Gen2 target properties:

Property	Description
Output Format	Select the format of the output file. Options are: - CSV - AVRO - PARQUET The default value is CSV if you do not use an Open Table format. If you select the Open table format, Parquet is selected by default for Apache Iceberg. Note: Output files in CSV format use double-quotation marks ("") as the delimiter for each field.
Add Headers to CSV File	If CSV is selected as the output format, select this check box to add a header with source column names to the output CSV file.
Parquet Compression Type	If the PARQUET output format is selected, you can select a compression type that is supported by Parquet. Options are: - None - Gzip - Snappy The default value is None, which means no compression is used.
Avro Format	If you selected AVRO as the output format, select the format of the Avro schema that will be created for each source table. Options are: - Avro-Flat. This Avro schema format lists all Avro fields in one record. - Avro-Generic. This Avro schema format lists all columns from a source table in a single array of Avro fields. - Avro-Nested. This Avro schema format organizes each type of information in a separate record. The default value is Avro-Flat.
Avro Serialization Format	If AVRO is selected as the output format, select the serialization format of the Avro output file. Options are: - None - Binary - JSON The default value is Binary.
Avro Schema Directory	If AVRO is selected as the output format, specify the local directory where Application Ingestion and Replication stores Avro schema definitions for each source table. Schema definition files have the following naming pattern: schemaname_tablename.txt Note: If this directory is not specified, no Avro schema definition file is produced.
File Compression Type	Select a file compression type for output files in CSV or AVRO output format. Options are: - None - Deflate - Gzip - Snappy The default value is None, which means no compression is used.
Avro Compression Type	If AVRO is selected as the output format, select an Avro compression type. Options are: - None - Bzip2 - Deflate - Snappy The default value is None, which means no compression is used.
Deflate Compression Level	If Deflate is selected in the Avro Compression Type field, specify a compression level from 0 to 9. The default value is 0.
Add Directory Tags	For incremental load and combined initial and incremental load tasks, select this check box to add the "dt=" prefix to the names of apply cycle directories to be compatible with the naming convention for Hive partitioning. This check box is cleared by default.
Task Target Directory	For incremental load and combined initial and incremental load tasks, the root directory for the other directories that hold output data files, schema files, and CDC cycle contents and completed files. You can use it to specify a custom root directory for the task. If you enable the Connection Directory as Parent option, you can still optionally specify a task target directory to use with the parent directory specified in the connection properties. This field is required if the {TaskTargetDirectory} placeholder is specified in patterns for any of the following directory fields.
Data Directory	For initial load tasks, define a directory structure for the directories where Application Ingestion and Replication stores output data files and optionally stores the schema. The default directory pattern is {TableName)_{Timestamp}. To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter a folder name or use variables to create a folder name. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the initial load job starts to transfer data to the target. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: If you manually enter the directory expression, ensure that you enclose placeholders with curly brackets { }. Placeholder values are not case sensitive. For example: myDir1/{SchemaName}/{TableName} myDir1/myDir2/{SchemaName}/{YYYY}/{MM}/{TableName}_{Timestamp} myDir1/{toLower(SchemaName)}/{TableName}_{Timestamp} For incremental load and combined initial and incremental load tasks, define a custom path to the subdirectory that contains the cdc-data data files. The default directory pattern is {TaskTargetDirectory}/data/{TableName}/data To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter {TaskTargetDirectory} for a task-specific base directory on the target to use instead of the S3 folder path specified in the connection properties. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the CDC cycle started. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: For Amazon S3 and Microsoft Azure Data Lake Storage Gen2 targets, Application Ingestion and Replication uses the directory specified in the target connection properties as the root for the data directory path when Connection Directory as Parent is selected. For Google Cloud Storage targets, Application Ingestion and Replication uses the Bucket name that you specify in the target properties for the ingestion task. For Microsoft Fabric OneLake targets, the parent directory is the path specified in the Lakehouse Path field in the Microsoft Fabric OneLake connection properties. For Amazon S3 targets with Open Table format, the data directory field is not applicable. Enabling the Connection Directory as Parent includes the connection directory before the warehouse base path. If disabled, files are saved directly under the warehouse base directory.
Connection Directory as Parent	Select this check box to use the directory value that is specified in the target connection properties as the parent directory for the custom directory paths specified in the task target properties. For initial load tasks, the parent directory is used in the Data Directory and Schema Directory. For incremental load and combined initial and incremental load tasks, the parent directory is used in the Data Directory, Schema Directory, Cycle Completion Directory, and Cycle Contents Directory. This check box is selected by default. If you clear it, for initial loads, define the full path to the output files in the Data Directory field. For incremental loads, optionally specify a root directory for the task in the Task Target Directory.
Schema Directory	Specify a custom directory in which to store the schema file if you want to store it in a directory other than the default directory. For initial loads, previously used values if available are shown in a list for your convenience. This field is optional. For initial loads, the schema is stored in the data directory by default. For incremental loads and combined initial and incremental loads, the default directory for the schema file is {TaskTargetDirectory}/data/{TableName}/schema You can use the same placeholders as for the Data Directory field. If you manually enter placeholders, ensure that you enclose them with curly brackets { }. If you include the toUpper or toLower function, put the placeholder name in parentheses and enclose both the function and placeholder in curly brackets, for example: {toLower(SchemaName)} Note: Schema is written only to output data files in CSV format. Data files in Parquet and Avro formats contain their own embedded schema.
Cycle Completion Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle completed file. Default is {TaskTargetDirectory}/cycle/completed.
Cycle Contents Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle contents files. Default is {TaskTargetDirectory}/cycle/contents.
Use Cycle Partitioning for Data Directory	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under each data directory. If this option is not selected, individual data files are written to the same directory without a timestamp, unless you define an alternative directory structure.
Use Cycle Partitioning for Summary Directories	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under the summary contents and completed subdirectories.
List Individual Files in Contents	For incremental load and combined initial and incremental load tasks, lists individual data files under the contents subdirectory. If Use Cycle Partitioning for Summary Directories is cleared, this option is selected by default. All of the individual files are listed in the contents subdirectory unless you can configure custom subdirectories by using the placeholders, such as for timestamp or date. If Use Cycle Partitioning for Data Directory is selected, you can still optionally select this check box to list individual files and group them by CDC cycle.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Operation Type	Select this check box to add a metadata column that records the source SQL operation type in the output that the job propagates to the target. For incremental loads, the job writes "I" for insert, "U" for update, or "D" for delete. For initial loads, the job always writes "I" for insert. By default, this check box is selected for incremental load and initial and incremental load jobs, and cleared for initial load jobs.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target. For initial loads, the job always writes the current date and time. By default, this check box is not selected.
Add Orderable Sequence	Select this check box to add a metadata column that records a combined epoch value and an incremental numeric value for each change operation that the job inserts into the target tables. The sequence value is always ascending, but not guaranteed to be sequential and gaps may exist. The sequence value is used to identify the order of activity in the target records. By default, this check box is not selected.
Add Before Images	Select this check box to include UNDO data in the output that a job writes to the target. For initial loads, the job writes nulls. By default, this check box is not selected.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed, or click Save.

Configure a Microsoft Azure Synapse Analytics target

1Under Target Properties, define the following required Microsoft Azure Synapse Analytics target properties:

Property	Description
Target Creation	The only available option is Create Target Tables, which generates the target tables based on the source objects.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables. The schema name that is specified in the connection properties is displayed by default. This field is case sensitive. Therefore, ensure that you entered the schema name in the connection properties in the correct case.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Last Replicated Time	Select this check box to add a metadata column that records the timestamp at which a record was inserted or last updated in the target table. For initial loads, all loaded records have the same timestamp. For incremental and combined initial and incremental loads, the column records the timestamp of the last DML operation that was applied to the target. By default, this check box is not selected.
Prefix for Metadata Columns	Add a prefix to the names of the added metadata columns to easily identify them and to prevent conflicts with the names of existing columns. Do not include special characters in the prefix. Otherwise, task deployment will fail. The default value is INFA_.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Configure a Microsoft Fabric OneLake target

1Under Target Properties, define the following required Microsoft Fabric OneLake target properties:

Property	Description
Output Format	Select the format of the output file. Options are: - CSV - AVRO - PARQUET The default value is CSV if you do not use an Open Table format. If you select the Open table format, Parquet is selected by default for Apache Iceberg. Note: Output files in CSV format use double-quotation marks ("") as the delimiter for each field.
Add Headers to CSV File	If CSV is selected as the output format, select this check box to add a header with source column names to the output CSV file.
Parquet Compression Type	If the PARQUET output format is selected, you can select a compression type that is supported by Parquet. Options are: - None - Gzip - Snappy The default value is None, which means no compression is used.
Avro Format	If you selected AVRO as the output format, select the format of the Avro schema that will be created for each source table. Options are: - Avro-Flat. This Avro schema format lists all Avro fields in one record. - Avro-Generic. This Avro schema format lists all columns from a source table in a single array of Avro fields. - Avro-Nested. This Avro schema format organizes each type of information in a separate record. The default value is Avro-Flat.
Avro Serialization Format	If AVRO is selected as the output format, select the serialization format of the Avro output file. Options are: - None - Binary - JSON The default value is Binary.
Avro Schema Directory	If AVRO is selected as the output format, specify the local directory where Application Ingestion and Replication stores Avro schema definitions for each source table. Schema definition files have the following naming pattern: schemaname_tablename.txt Note: If this directory is not specified, no Avro schema definition file is produced.
File Compression Type	Select a file compression type for output files in CSV or AVRO output format. Options are: - None - Deflate - Gzip - Snappy The default value is None, which means no compression is used.
Avro Compression Type	If AVRO is selected as the output format, select an Avro compression type. Options are: - None - Bzip2 - Deflate - Snappy The default value is None, which means no compression is used.
Deflate Compression Level	If Deflate is selected in the Avro Compression Type field, specify a compression level from 0 to 9. The default value is 0.
Add Directory Tags	For incremental load and combined initial and incremental load tasks, select this check box to add the "dt=" prefix to the names of apply cycle directories to be compatible with the naming convention for Hive partitioning. This check box is cleared by default.
Task Target Directory	For incremental load and combined initial and incremental load tasks, the root directory for the other directories that hold output data files, schema files, and CDC cycle contents and completed files. You can use it to specify a custom root directory for the task. This field is required if the {TaskTargetDirectory} placeholder is specified in patterns for any of the following directory fields.
Data Directory	For initial load tasks, define a directory structure for the directories where Application Ingestion and Replication stores output data files and optionally stores the schema. The default directory pattern is {TableName)_{Timestamp}. To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter a folder name or use variables to create a folder name. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the initial load job starts to transfer data to the target. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: If you manually enter the directory expression, ensure that you enclose placeholders with curly brackets { }. Placeholder values are not case sensitive. For example: myDir1/{SchemaName}/{TableName} myDir1/myDir2/{SchemaName}/{YYYY}/{MM}/{TableName}_{Timestamp} myDir1/{toLower(SchemaName)}/{TableName}_{Timestamp} For incremental load and combined initial and incremental load tasks, define a custom path to the subdirectory that contains the cdc-data data files. The default directory pattern is {TaskTargetDirectory}/data/{TableName}/data To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter {TaskTargetDirectory} for a task-specific base directory on the target to use instead of the S3 folder path specified in the connection properties. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the CDC cycle started. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: For Amazon S3 and Microsoft Azure Data Lake Storage Gen2 targets, Application Ingestion and Replication uses the directory specified in the target connection properties as the root for the data directory path when Connection Directory as Parent is selected. For Google Cloud Storage targets, Application Ingestion and Replication uses the Bucket name that you specify in the target properties for the ingestion task. For Microsoft Fabric OneLake targets, the parent directory is the path specified in the Lakehouse Path field in the Microsoft Fabric OneLake connection properties. For Amazon S3 targets with Open Table format, the data directory field is not applicable. Enabling the Connection Directory as Parent includes the connection directory before the warehouse base path. If disabled, files are saved directly under the warehouse base directory.
Schema Directory	Specify a custom directory in which to store the schema file if you want to store it in a directory other than the default directory. For initial loads, previously used values if available are shown in a list for your convenience. This field is optional. For initial loads, the schema is stored in the data directory by default. For incremental loads and combined initial and incremental loads, the default directory for the schema file is {TaskTargetDirectory}/data/{TableName}/schema You can use the same placeholders as for the Data Directory field. If you manually enter placeholders, ensure that you enclose them with curly brackets { }. If you include the toUpper or toLower function, put the placeholder name in parentheses and enclose both the function and placeholder in curly brackets, for example: {toLower(SchemaName)} Note: Schema is written only to output data files in CSV format. Data files in Parquet and Avro formats contain their own embedded schema.
Cycle Completion Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle completed file. Default is {TaskTargetDirectory}/cycle/completed.
Cycle Contents Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle contents files. Default is {TaskTargetDirectory}/cycle/contents.
Use Cycle Partitioning for Data Directory	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under each data directory. If this option is not selected, individual data files are written to the same directory without a timestamp, unless you define an alternative directory structure.
Use Cycle Partitioning for Summary Directories	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under the summary contents and completed subdirectories.
List Individual Files in Contents	For incremental load and combined initial and incremental load tasks, lists individual data files under the contents subdirectory. If Use Cycle Partitioning for Summary Directories is cleared, this option is selected by default. All of the individual files are listed in the contents subdirectory unless you can configure custom subdirectories by using the placeholders, such as for timestamp or date. If Use Cycle Partitioning for Data Directory is selected, you can still optionally select this check box to list individual files and group them by CDC cycle.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any optional advanced target properties that you want to use.
3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed, or click Save.

Configure a Microsoft SQL Server target

1Under Target Properties, define the following target properties.

Property	Description
Target Creation	The Create Target Tables option generates the target tables based on the source tables. Note: After the target table is created, Application Ingestion and Replication intelligently handles the target tables on subsequent job runs. Application Ingestion and Replication might truncate or re-create the target tables depending on specific circumstances.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables. The schema name that is specified in the connection properties is displayed by default. This field is case sensitive. Therefore, ensure that you entered the schema name in the connection properties in the correct case.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Property	Description
Add Last Replicated Time	Select this check box to add a metadata column that records the timestamp at which a record was inserted or last updated in the target table. For initial loads, all loaded records have the same timestamp. For incremental and combined initial and incremental loads, the column records the timestamp of the last DML operation that was applied to the target. By default, this check box is not selected.
Add Cycle ID	Select this check box to add a metadata column that includes the cycle ID of each CDC cycle in each target table. A cycle ID is a number that's generated by the CDC engine for each successful CDC cycle. If you integrate the job with Data Integration taskflows, the job can pass the minimum and maximum cycle IDs in output fields to the taskflow so that the taskflow can determine the range of cycles that contain new CDC data. This capability is useful if data from multiple cycles accumulates before the previous taskflow run completes. By default, this check box is not selected.
Prefix for Metadata Columns	Add a prefix to the names of the added metadata columns to easily identify them and to prevent conflicts with the names of existing columns. Do not include special characters in the prefix. Otherwise, task deployment will fail. The default value is INFA_.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can enter one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available for this target:

Property	Description
Writer Distributor Count	The number of distributors that can run on separate threads in parallel to process data during an initial load job or the unload phase of a combined load job when the Writer Unload Multiple Distributors custom property is set to true. Using parallel distributor threads can improve job performance, particularly for high-volume data transfers. Default value is 3. If your system has ample resources, Informatica recommends that you set this parameter to 8.
Writer Unload Multiple Distributors	Indicates whether multiple distributor threads can be used to process data in parallel during initial load jobs and the unload phase of combined load jobs. The distributors perform work such as uploading data files to staging areas and flushing data to the target. Set this property to true to use multiple distributor threads. Default value is false.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Configure an Oracle Cloud Object Storage target

1Under Target Properties, define the following required Oracle Cloud Object Storage target properties:

Property	Description
Output Format	Select the format of the output file. Options are: - CSV - AVRO - PARQUET The default value is CSV if you do not use an Open Table format. If you select the Open table format, Parquet is selected by default for Apache Iceberg. Note: Output files in CSV format use double-quotation marks ("") as the delimiter for each field.
Add Headers to CSV File	If CSV is selected as the output format, select this check box to add a header with source column names to the output CSV file.
Parquet Compression Type	If the PARQUET output format is selected, you can select a compression type that is supported by Parquet. Options are: - None - Gzip - Snappy The default value is None, which means no compression is used.
Avro Format	If you selected AVRO as the output format, select the format of the Avro schema that will be created for each source table. Options are: - Avro-Flat. This Avro schema format lists all Avro fields in one record. - Avro-Generic. This Avro schema format lists all columns from a source table in a single array of Avro fields. - Avro-Nested. This Avro schema format organizes each type of information in a separate record. The default value is Avro-Flat.
Avro Serialization Format	If AVRO is selected as the output format, select the serialization format of the Avro output file. Options are: - None - Binary - JSON The default value is Binary.
Avro Schema Directory	If AVRO is selected as the output format, specify the local directory where Application Ingestion and Replication stores Avro schema definitions for each source table. Schema definition files have the following naming pattern: schemaname_tablename.txt Note: If this directory is not specified, no Avro schema definition file is produced.
File Compression Type	Select a file compression type for output files in CSV or AVRO output format. Options are: - None - Deflate - Gzip - Snappy The default value is None, which means no compression is used.
Avro Compression Type	If AVRO is selected as the output format, select an Avro compression type. Options are: - None - Bzip2 - Deflate - Snappy The default value is None, which means no compression is used.
Deflate Compression Level	If Deflate is selected in the Avro Compression Type field, specify a compression level from 0 to 9. The default value is 0.
Add Directory Tags	For incremental load and combined initial and incremental load tasks, select this check box to add the "dt=" prefix to the names of apply cycle directories to be compatible with the naming convention for Hive partitioning. This check box is cleared by default.
Task Target Directory	For incremental load and combined initial and incremental load tasks, the root directory for the other directories that hold output data files, schema files, and CDC cycle contents and completed files. You can use it to specify a custom root directory for the task. If you enable the Connection Directory as Parent option, you can still optionally specify a task target directory to use with the parent directory specified in the connection properties. This field is required if the {TaskTargetDirectory} placeholder is specified in patterns for any of the following directory fields.
Connection Directory as Parent	Select this check box to use the directory value that is specified in the target connection properties as the parent directory for the custom directory paths specified in the task target properties. For initial load tasks, the parent directory is used in the Data Directory and Schema Directory. For incremental load and combined initial and incremental load tasks, the parent directory is used in the Data Directory, Schema Directory, Cycle Completion Directory, and Cycle Contents Directory. This check box is selected by default. If you clear it, for initial loads, define the full path to the output files in the Data Directory field. For incremental loads, optionally specify a root directory for the task in the Task Target Directory.
Data Directory	For initial load tasks, define a directory structure for the directories where Application Ingestion and Replication stores output data files and optionally stores the schema. The default directory pattern is {TableName)_{Timestamp}. To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter a folder name or use variables to create a folder name. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the initial load job starts to transfer data to the target. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: If you manually enter the directory expression, ensure that you enclose placeholders with curly brackets { }. Placeholder values are not case sensitive. For example: myDir1/{SchemaName}/{TableName} myDir1/myDir2/{SchemaName}/{YYYY}/{MM}/{TableName}_{Timestamp} myDir1/{toLower(SchemaName)}/{TableName}_{Timestamp} For incremental load and combined initial and incremental load tasks, define a custom path to the subdirectory that contains the cdc-data data files. The default directory pattern is {TaskTargetDirectory}/data/{TableName}/data To customize the directory pattern, click the Edit icon to select from the following listed path types and values: - Folder Path. Enter {TaskTargetDirectory} for a task-specific base directory on the target to use instead of the S3 folder path specified in the connection properties. - Timestamp values. Select data elements Timestamp, yy, yyyy, mm, or dd. The Timestamp values are in the format yyyymmdd_hhmissms. The generated dates and times in the directory paths indicate when the CDC cycle started. - Schema Name. Select SchemaName, toUpper(SchemaName), or toLower(SchemaName). - Table Name. Select TableName, toUpper(TableName), and toLower(TableName). Note: For Amazon S3 and Microsoft Azure Data Lake Storage Gen2 targets, Application Ingestion and Replication uses the directory specified in the target connection properties as the root for the data directory path when Connection Directory as Parent is selected. For Google Cloud Storage targets, Application Ingestion and Replication uses the Bucket name that you specify in the target properties for the ingestion task. For Microsoft Fabric OneLake targets, the parent directory is the path specified in the Lakehouse Path field in the Microsoft Fabric OneLake connection properties. For Amazon S3 targets with Open Table format, the data directory field is not applicable. Enabling the Connection Directory as Parent includes the connection directory before the warehouse base path. If disabled, files are saved directly under the warehouse base directory.
Schema Directory	Specify a custom directory in which to store the schema file if you want to store it in a directory other than the default directory. For initial loads, previously used values if available are shown in a list for your convenience. This field is optional. For initial loads, the schema is stored in the data directory by default. For incremental loads and combined initial and incremental loads, the default directory for the schema file is {TaskTargetDirectory}/data/{TableName}/schema You can use the same placeholders as for the Data Directory field. If you manually enter placeholders, ensure that you enclose them with curly brackets { }. If you include the toUpper or toLower function, put the placeholder name in parentheses and enclose both the function and placeholder in curly brackets, for example: {toLower(SchemaName)} Note: Schema is written only to output data files in CSV format. Data files in Parquet and Avro formats contain their own embedded schema.
Cycle Completion Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle completed file. Default is {TaskTargetDirectory}/cycle/completed.
Cycle Contents Directory	For incremental load and combined initial and incremental load tasks, the path to the directory that contains the cycle contents files. Default is {TaskTargetDirectory}/cycle/contents.
Use Cycle Partitioning for Data Directory	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under each data directory. If this option is not selected, individual data files are written to the same directory without a timestamp, unless you define an alternative directory structure.
Use Cycle Partitioning for Summary Directories	For incremental load and combined initial and incremental load tasks, causes a timestamp subdirectory to be created for each CDC cycle, under the summary contents and completed subdirectories.
List Individual Files in Contents	For incremental load and combined initial and incremental load tasks, lists individual data files under the contents subdirectory. If Use Cycle Partitioning for Summary Directories is cleared, this option is selected by default. All of the individual files are listed in the contents subdirectory unless you can configure custom subdirectories by using the placeholders, such as for timestamp or date. If Use Cycle Partitioning for Data Directory is selected, you can still optionally select this check box to list individual files and group them by CDC cycle.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Field	Description
Add Operation Type	Select this check box to add a metadata column that records the source SQL operation type in the output that the job propagates to the target. For incremental loads, the job writes "I" for insert, "U" for update, or "D" for delete. For initial loads, the job always writes "I" for insert. By default, this check box is selected for incremental load and initial and incremental load jobs, and cleared for initial load jobs.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target. For initial loads, the job always writes the current date and time. By default, this check box is not selected.
Add Orderable Sequence	Select this check box to add a metadata column that records a combined epoch value and an incremental numeric value for each change operation that the job inserts into the target tables. The sequence value is always ascending, but not guaranteed to be sequential and gaps may exist. The sequence value is used to identify the order of activity in the target records. By default, this check box is not selected.
Add Before Images	Select this check box to include UNDO data in the output that a job writes to the target. By default, this check box is not selected.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
5Click Next to proceed, or click Save.

Configure an Oracle target

1Under Target Properties, define the following target properties:

Property	Description
Target Creation	The only available option is Create Target Tables, which generates the target tables based on the source objects.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables.
Apply Mode	For incremental load and combined initial and incremental load jobs, indicates how source DML changes, including inserts, updates, and deletes, are applied to the target. Options are: - Standard. Accumulate the changes in a single apply cycle and intelligently merge them into fewer SQL statements before applying them to the target. For example, if an update followed by a delete occurs on the source row, no row is applied to the target. If multiple updates occur on the same column or field, only the last update is applied to the target. If multiple updates occur on different columns or fields, the updates are merged into a single update record before being applied to the target. - Audit. Apply an audit trail of every DML operation made on the source tables to the target. A row for each DML change on a source table is written to the generated target table along with the audit columns you select under the Advanced section. The audit columns contain metadata about the change, such as the DML operation type, time, owner, transaction ID, generated ascending sequence number, and before image. Consider using Audit apply mode when you want to use the audit history to perform downstream computations or processing on the data before writing it to the target database or when you want to examine metadata about the captured changes. Note: The Audit apply mode applies for an SAP source with SAP Mass Ingestion connector. The default value is Standard.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Field	Description
Add Last Replicated Time	Select this check box to add a metadata column that records the timestamp in UTC format at which a record was inserted or last updated in the target table. For initial loads, all loaded records have the same timestamp. For incremental and combined initial and incremental loads, the column records the timestamp of the last DML operation that was applied to the target. By default, this check box is not selected.
Add Operation Type	Select this check box to add a metadata column that records the source SQL operation type in the output that the job propagates to the target database or inserts into the target table. The job writes "I" for insert, "U" for update, or "D" for delete. By default, this check box is selected.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target table. By default, this check box is not selected.
Add Operation Sequence	Select this check box to add a metadata column that records a generated, ascending sequence number for each change operation that the job inserts into the target tables. The sequence number reflects the change stream position of the operation. By default, this check box is not selected.
Add Before Images	Select this check box to add _OLD columns with UNDO "before image" data in the output that the job inserts into the target tables. You can then compare the old and current values for each data column. For a delete operation, the current value will be null. By default, this check box is not selected.
Add Cycle ID	Select this check box to add a metadata column that includes the cycle ID of each CDC cycle in each target table. A cycle ID is a number that's generated by the CDC engine for each successful CDC cycle. If you integrate the job with Data Integration taskflows, the job can pass the minimum and maximum cycle IDs in output fields to the taskflow so that the taskflow can determine the range of cycles that contain new CDC data. This capability is useful if data from multiple cycles accumulates before the previous taskflow run completes. By default, this check box is not selected.
Prefix for Metadata Columns	Add a prefix to the names of the added metadata columns to easily identify them and to prevent conflicts with the names of existing columns. The default value is INFA_.
Enable Case Transformation	By default, target table names and column names are generated in the same case as the corresponding source names. If you want to control the case of letters in the target names, select this check box. Then select a Case Transformation Strategy option.
Case Transformation Strategy	If you selected Enable Case Transformation, select one of the following options to specify how to handle the case of letters in generated target table (or object) names and column (or field) names: - Same as source. Use the same case as the source table (or object) names and column (or field) names. - UPPERCASE. Use all uppercase. - lowercase. Use all lowercase. The default value is Same as source.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can enter one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available for this target:

Property	Description
Writer Distributor Count	The number of distributors that can run on separate threads in parallel to process data during an initial load job or the unload phase of a combined load job when the Writer Unload Multiple Distributors custom property is set to true. Using parallel distributor threads can improve job performance, particularly for high-volume data transfers. Default value is 3. If your system has ample resources, Informatica recommends that you set this parameter to 8.
Writer Unload Multiple Distributors	Indicates whether multiple distributor threads can be used to process data in parallel during initial load jobs and the unload phase of combined load jobs. The distributors perform work such as uploading data files to staging areas and flushing data to the target. Set this property to true to use multiple distributor threads. Default value is false.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Configure a PostgreSQL target

1Under Target Properties, define the following required PostgreSQL target properties:

Property	Description
Target Creation	The only available option is Create Target Tables, which generates the target tables based on the source objects.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any optional advanced target properties that you want to use.
3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can enter one or more custom properties that Informatica provides to improve performance or to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select a property and then enter a property value, or select the Custom option and manuallly enter both the property name and value.
The following table describes the properties that are available for this target:

Property	Description
Writer Distributor Count	The number of distributors that can run on separate threads in parallel to process data during an initial load job or the unload phase of a combined load job when the Writer Unload Multiple Distributors custom property is set to true. Using parallel distributor threads can improve job performance, particularly for high-volume data transfers. Default value is 3. If your system has ample resources, Informatica recommends that you set this parameter to 8.
Writer Unload Multiple Distributors	Indicates whether multiple distributor threads can be used to process data in parallel during initial load jobs and the unload phase of combined load jobs. The distributors perform work such as uploading data files to staging areas and flushing data to the target. Set this property to true to use multiple distributor threads. Default value is false.
Custom	Select this option to manually enter the name of a property and its value. Use this option to enter properties that Informatica Global Customer Support or a technical staff member has provided to you for a special case. Available for any supported load type.

Custom properties are intended to address performance or special processing needs. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Configure a Snowflake Cloud Data Warehouse target

1Under Target Properties, define the following required Snowflake target properties:

Property	Description
Target Creation	The only available option is Create Target Tables, which generates the target tables based on the source objects.
Schema	Select the target schema in which Application Ingestion and Replication creates the target tables.
Stage	The name of internal staging area that holds the data read from the source before the data is written to the target tables. This name must not include spaces. If the staging area does not exist, it will be automatically created. Note: This field is not available if you selected the Superpipe option in the Advanced Target Properties.
Apply Mode	For incremental load and combined initial and incremental load jobs, indicates how source DML changes, including inserts, updates, and deletes, are applied to the target. Options are: - Standard. Accumulate the changes in a single apply cycle and intelligently merge them into fewer SQL statements before applying them to the target. For example, if an update followed by a delete occurs on the source row, no row is applied to the target. If multiple updates occur on the same column or field, only the last update is applied to the target. If multiple updates occur on different columns or fields, the updates are merged into a single update record before being applied to the target. - Soft Deletes. Apply source delete operations to the target as soft deletes. A soft delete marks the deleted row as deleted without actually removing it from the database. For example, a delete on the source results in a change record on the target with "D" displayed in the INFA_OPERATION_TYPE column. After enabling Soft Deletes, any update in the source table during normal or backlog mode results in the deletion of the matching record, insertion of the updated record, and marking of the INFA_OPERATION_TYPE operation as NULL in the target table. Similarly, inserting a record in the source table during backlog mode results in marking the INFA_OPERATION_TYPE operation as E in the target table record. Consider using soft deletes if you have a long-running business process that needs the soft-deleted data to finish processing, to restore data after an accidental delete operation, or to track deleted values for audit purposes. - Audit. Apply an audit trail of every DML operation made on the source tables to the target. A row for each DML change on a source table is written to the generated target table along with the audit columns you select under the Advanced section. The audit columns contain metadata about the change, such as the DML operation type, transaction ID, and before image. Consider using Audit apply mode when you want to use the audit history to perform downstream computations or processing on the data before writing it to the target database or when you want to examine metadata about the captured changes. After enabling the Audit apply mode, any update in the source table during backlog or normal mode results in marking the INFA_OPERATION_TYPE operation as E in the target table record. Similarly, inserting a record in the source table during backlog mode results in marking the INFA_OPERATION_TYPE operation as E in the target table record. Note: The Audit apply mode applies for SAP source with SAP Mass Ingestion connector. Default is Standard.

2To view advanced properties, toggle on Show Advanced Options. Then under Advanced Target Properties, define any of the following optional advanced target properties that you want to use:

Field	Description
Add Last Replicated Time	Select this check box to add a metadata column that records the timestamp at which a record was inserted or last updated in the target table. For initial loads, all loaded records have the same timestamp, except for Snowflake targets that use the Superpipe option where minutes and seconds might vary slightly. For incremental and combined initial and incremental loads, the column records the timestamp of the last DML operation that was applied to the target. By default, this check box is not selected.
Add Operation Type	Add a metadata column that includes the source SQL operation type in the output that the job propagates to the target tables. The column is named INFA_OPERATION_TYPE by default. This field is displayed only when the Apply Mode option is set to Audit or Soft Deletes. In Audit mode, the job writes "I" for inserts, "U" for updates, "E" for upserts, or "D" for deletes to this metadata column. In Soft Deletes mode, the job writes "D" for deletes or NULL for inserts and updates. When the operation type is NULL, the other "Add Operation..." metadata columns are also NULL. Only when the operation type is "D" will the other metadata columns contain non-null values. By default, this check box is selected. You cannot deselect it.
Add Operation Time	Select this check box to add a metadata column that records the source SQL operation timestamp in the output that the job propagates to the target tables. This field is available only when Apply Mode is set to Audit or Soft Deletes. By default, this check box is not selected.
Add Operation Sequence	Select this check box to add a metadata column that records a generated, ascending sequence number for each change operation that the job inserts into the target tables. The sequence number reflects the change stream position of the operation. This field is available only when Apply Mode is set to Audit. By default, this check box is not selected.
Add Before Images	Select this check box to add _OLD columns with UNDO "before image" data in the output that the job inserts into the target tables. You can then compare the old and current values for each data column. For a delete operation, the current value will be null. This field is available only when Apply Mode is set to Audit. By default, this check box is not selected.
Add Cycle ID	Select this check box to add a metadata column that includes the cycle ID of each CDC cycle in each target table. A cycle ID is a number that's generated by the CDC engine for each successful CDC cycle. If you integrate the job with Data Integration taskflows, the job can pass the minimum and maximum cycle IDs in output fields to the taskflow so that the taskflow can determine the range of cycles that contain new CDC data. This capability is useful if data from multiple cycles accumulates before the previous taskflow run completes. By default, this check box is not selected. Note: If you select this option, you can't also select the Superpipe option for the Snowflake target.
Prefix for Metadata Columns	Add a prefix to the names of the added metadata columns to easily identify them and to prevent conflicts with the names of existing columns. The default value is INFA_.
Superpipe	Select this check box to use the Snowpipe Streaming API to quickly stream rows of data directly to Snowflake Data Cloud target tables with low latency instead of first writing the data to stage files. This option is available for all load types. When you configure the target connection, select KeyPair authentication. By default, this check box is selected. Deselect it if you want to write data to intermediate stage files. Note: If you enable the Superpipe option for a task that uses the Soft Deletes apply mode, make sure the source tables contain a primary key.
Merge Frequency	When Superpipe is selected, you can optionally set the frequency, in seconds, at which change data rows are merged and applied to the Snowflake target tables. The merge frequency affects how often the stream change data is merged to the Snowflake base table. A Snowflake view joins the stream change data with the base table. Set this value to balance the costs of merging data to the base table with the performance of view join processing. This field applies to incremental load and combined initial and incremental load tasks. Valid values are 60 through 604800 seconds. Default is 3600 seconds.
Enable Case Transformation	By default, target table names and column names are generated in the same case as the corresponding source names, unless cluster-level or session-level properties on the target override this case-sensitive behavior. If you want to control the case of letters in the target names, select this check box. Then select a Case Transformation Strategy option.
Case Transformation Strategy	If you selected Enable Case Transformation, select one of the following options to specify how to handle the case of letters in generated target table (or object) names and column (or field) names: - Same as source. Use the same case as the source table (or object) names and column (or field) names. - UPPERCASE. Use all uppercase. - lowercase. Use all lowercase. The default value is Same as source. Note: The selected strategy will override any cluster-level or session-level properties on the target for controlling case.

3Under Table Renaming Rules, if you want to rename the target objects that are associated with the selected source tables, define renaming rules. Click the + (Add new row) icon and enter a source table name or name mask and enter a corresponding target table name or name mask. To define a mask, include one or more the asterisk (*) wildcards. Then press Enter.
For example, to add the prefix "PROD_" to the names of target tables that correspond to all selected source tables, enter the * wildcard for the source table and enter PROD_* for the target table.
You can enter multiple rules.
Notes:
• - If you enter the wildcard for a source table mask, you must also enter the wildcard for a target table mask.
• - If a table name includes special characters, such as a backslash (\), asterisk(*), dot (.), or question mark (?), escape each special character in the name with a backslash (\).
• - On Windows, if you enter target table renaming criteria that causes a target table name to exceed 232 characters in length, the name is truncated to 222 characters. Data Ingestion and Replication appends 14 characters to the name to add a date-time yyyyMMddHHmmss value, which causes the name to exceed the Windows maximum limit of 255. Ensure that the names of any renamed target tables will not exceed 232 characters.
4Under Data Type Rules, if you want to override the default mappings of source data types to target data types, define data type rules. Click the + (Add new row) icon and enter a source data type and corresponding target data type. Then press Enter.
Also, in the Source Data Type value, you can include the percent (%) wildcard to represent the data type precision, scale, or size, for example, NUMBER(%,4), NUMBER(8,%), or NUMBER(%). Use the wildcard to cover all source columns that have the same data type but use different precision, scale, or size values, instead of specifying each one individually. For example, enter FLOAT(%) to cover FLOAT(16), FLOAT(32), and FLOAT(84). You cannot enter the % wildcard in the target data type. A source data type that uses the % wildcard must map to a target data type that uses specific precision, scale, or size value. For example, you could map the source data type FLOAT(%) to a target data type specification such as NUMBER(38,10)
5Under Custom Properties, you can specify one or more custom properties that Informatica provides to meet your special requirements. To add a property, click the + icon to add a row. In the Property Name field, select the Custom option and manuallly enter both the property name and value.
Specify these properties only at the direction of Informatica Global Customer Support. Usually, these properties address unique environments or special processing needs. You can specify multiple properties, if necessary. A property name can contain only alphanumeric characters and the following special characters: periods (.), hyphens (-), and underscores (_).
Tip: To delete a custom property after you've entered it, click the Delete icon at the right end of the property row.
6Click Next to proceed, or click Save.

Transform the data

1On the Transform Data page, select the tables and columns to which you want to assign a transformation.
Note: You can apply trim transformations and row-level filters to the same tables and columns.
2To add a trim transformation, click Add Transformation.
The How do you want to transform your data? dialog box appears.
3Click the + (Add a new row) icon to add a row. Then, in the Transformation Type list, select one of the following options:
• - Trim Left. Trim spaces to the left of character column values.
• - Trim Right. Trim spaces to the right of character column values.
• - Trim. Trim spaces to the left of and to the right of character column values.
Click the Save icon to add the entry.
4Click Next to go to the Summary tab where you can review your transformation settings.
5If the settings are correct on the Summary tab, click Save to save them and return to the initial Transform Data page.

6To add another transformation type for a different table or set of tables, repeat steps 1 through 5.
Tip: You can remove a transformation assignment on the Transform Data page. Select the table with the unwanted transformation and click Clear All.
7To add row-level filters to the selected tables and columns, click the down arrow next to Add Transformation and select Add Row Filter.
The Add Row Filter option is available only only for application ingestion and replication tasks that have an SAP source (with an Oracle or HANA database) and use the SAP Mass Ingestion connector or that have a Salesforce source and use the Salesforce Mass Ingestion connector. The tasks can use any load type.

The How do you want to filter your data? dialog box appears.
8Select the table and filter type to apply the filter conditions.
1. aFrom the set of tables you previously selected, select the table that you want to assign a filter to.
2. bSelect one of the following filter types:
• ▪ Basic
• ▪ Advanced
The default option is Basic.
9To add a Basic filter, complete the following substeps:
1. aClick the + (Add a new row) icon to add a row.
2. bUnder Column Name, select a column.
Columns with unsupported data types for row filtering are marked as "Not supported."
3. cUnder Operator, select an operator type to use with the value.
4. dUnder Value, select or enter a value, depending on the column type. Then click the Save icon on the right end of the row to save the condition.
The following table describes the values that are valid for each column data type supported for filtering:

Column data type	Description
INTEGER	Enter a numeric value. You can use "+" and "-" only once before the number. The value must be between -2147483648 and 2147483647.
LONG	Enter a numeric value. You can use "+" and "-" only once before the number. The value must be between -9,223,372,036,854,775,808 and 9,223,372,036,854,775,807.
BIGINT	Enter a numeric value. You can use "+" and "-" only once before the number. Maximum length is 50 digits.
BIGDEC	Enter a numeric value. You can use "+" and "-" only once before the number. A decimal is allowed. Maximum length is 50 digits.
STRING	Enter text.
DATE	Use the date picker to select the date.
TIME	Enter the value in the format HH:MM:SS.MS, with milliseconds being optional and up to a maximum length is 9 digits. For example, 13:14:15.123456789
DATETIME	Use the date picker to select the date and time.
OFFSET_DATETIME	Use the date picker to select the date, time, and time zone.

Note: Application Ingestion and Replication does not support BOOLEAN, BINARY, BLOB, CLOB, and graphic column data types.
5. eClick Validate to test the syntax of the specified condition.
6. fTo add another Basic condition, repeat steps a through e.
The AND operator is used to combine the multiple conditions.
7. gClick Save to validate and save the changes.
8. hWhen done defining Basic filter conditions, click OK to return to the Transform Data page.
10To define an Advanced filter that consists of multiple conditions combined with the AND or OR operator, manually enter the conditions in the box.
Note: If you entered a Basic filter conditions for a column and then switched to the Advanced filter, the Basic condition is displayed so that you can add to it to make a more complex filter.
1. aUnder Column Name, select a column and click the > arrow.
The column name appears in the Filter Condition box.
Note: For combined load tasks, do not include columns that you expect will be updated during CDC processing. If the column is updated, it might become ineligible for replication and cause unpredictable results. In this case, you'd need to Resync the job.
2. bIn the Filter Condition box, type one or more conditions for the selected column. Manually enter conditions using the supported syntax and the appropriate operators, which can vary based on the column data type. You can also nest conditions using parentheses. See Syntax for row-level filtering. When done, click the Save icon on the right end of the row to save the advanced filter.
The following table describes the values that are valid for each column data type supported for filtering:

Column data type	Description
INTEGER	Enter a numeric value. You can use "+" and "-" only once before the number. The value must be between -2147483648 and 2147483647.
LONG	Enter a numeric value. You can use "+" and "-" only once before the number. The value must be between -9,223,372,036,854,775,808 and 9,223,372,036,854,775,807.
BIGINT	Enter a number value. You can use "+" and "-" only once before the number. Maximum length is 50 digits.
BIGDEC	Enter a numeric value. You can use "+" and "-" only once before the number. A decimal is allowed. Maximum length is 50 digits.
STRING	Enter an input attribute in single quotes (').
DATE	Enter the value in the format YYYY-MM-DD. Enter the input attribute in single quotes (').
TIME	Enter the value in the format HH:MM:SS.MS, with milliseconds (MS) being optional and up to a maximum length is 9 digits. Enter the input attribute in single quotes ('). For example, 13:14:15.123456789
DATETIME	Enter the date and time in the following format: YYYY-MM-DDTHH:MM:SS:MS For example, 2024-12-31T03:04:05.123456789 Enter the input attribute in single quotes (').
OFFSET_DATETIME	Enter the date, time, and time zone in the following format: YYYY-MM-DDTHH:MM:SS.MS+05:00 For example, 2024-03-15T10:03:04.123456789+05:00 Enter the input attribute in single quotes (').

Notes:
• ▪ Application Ingestion and Replication does not support BOOLEAN, BINARY, BLOB, CLOB, and graphic column data types.
• ▪ All date, time, and datetime values are matched against the source date and time. Time changes between Daylight Saving Time and standard time are not accommodated.
3. cClick Validate to test the syntax of the specified conditions.
Note: Switching from Advanced to Basic filter type after creating or editing an Advanced filter condition, deletes all changes to the filter condition, even if you saved it.
4. dClick Save to validate and save the changes and then click OK to return to the Transform Data page.
Note: Do not modify any column included in the filter after the task has been deployed. If you do so, the row-level filtering might not work properly.
The Filters column on the Transform Data page shows the applied filters as hyperlinks. Clicking the link opens the selected filter in edit mode. Tables with an advanced filter display Advanced next to their filter conditions in the Filters column.
On the Transform Data page, clicking the Clear All button at the top right hand corner removes all filters, including trim transformations and row-level filters from the selected tables.
11When done, click Next.

Syntax for row-level filtering