Step 2. Configure capabilities

Configure metadata extraction

1In the Connection and Runtime area, choose a serverless runtime environment or the Secure Agent group where you want to run catalog source jobs.
Note:
Serverless runtime environment options are available if the catalog source works with a serverless runtime environment.
2Choose to retain, delete, or deprecate objects that are deleted from the source system in the catalog with the Metadata Change Option.
• - Retain. Retains objects that are deleted from the source system in the catalog. If you update or add a filter, the catalog retains objects extracted from the previous job and extracts additional objects that match the current filter. Objects deleted from the source system are not deleted from the catalog. Enrichments added on deleted objects and relationships are retained.
• - Delete. Deletes metadata from the catalog based on objects deleted from the source system and changes you make to the filter. Enrichments added on deleted objects and relationships are also permanently lost. Objects renamed in the source system are removed and recreated in the catalog.
• - Deprecate. The lifecycle of objects imported into the catalog moves to Obsolete based on objects deleted from the source system and changes you make to the filter. This does not impact enrichments added on deprecated objects and relationships. Objects renamed in the source system are removed and recreated in the catalog. When you run the catalog source job again for other capabilities such as data classification, relationship discovery, or glossary association, the job doesn't consider obsolete objects. Obsolete objects remain in the catalog until they are purged when you run a Purge Obsolete Objects job on the Explore page.
Note:
You can also change the configured metadata change option when you run a catalog source.
3In the Filters area, define one or more filter conditions to apply for metadata extraction:
1. aSelect Yes to view filter options.
2. bFrom the Include/Exclude list, choose to include or exclude metadata based on the filter parameters.
3. cFrom the Object type list, select CRM, Data 360, or Flows.
4. dFrom the Filter criteria, select the object that you want to extract metadata from.
• ▪ For CRM object type, select Object, using API name or ListView, using API name as the filter criteria.
• ▪ For Data 360 object type, select All types, Calculated Insight, Data Lake Object, Data Model Object, Data Stream, Data Transform, or Identity Resolution as the filter criteria.
• ▪ For Flows object type, select All Types as the filter criteria.
5. eEnter a value to specify the object location.
Filters can contain the following wildcards:
• ▪ Question mark. Represents a single character.
• ▪ Asterisk. Represents multiple characters or empty text.
When you enter values for filters, enclose them in double quotes if the value includes an asterisk or spaces before or after a string value.
The following image shows the filter condition options:
Examples:
• ▪ To include or exclude metadata from all Salesforce CRM list views with the API name 'Finance', select CRM as the object type and ListView, using API name as the filter criteria, and then enter Finance in the value field.
• ▪ To include or exclude metadata from all Salesforce CRM objects with the API name that begins with 'Finance', select CRM as the object type and Object, using API name as the filter criteria, and then enter Finance* in the value field.
• ▪ To include or exclude metadata from all Salesforce Data 360 delta lake objects that begin with the name 'Account', select Data 360 as the object type and Data Lake Object as the filter criteria, and then enter Account* in the value field.
• ▪ To include or exclude metadata from all Salesforce Data 360 calculated insights with names that start with 'SalesOrders' followed by a single character, select Data 360 as the object type and Calculated Insight as the filter criteria, and then enter SalesOrders? in the value field.
• ▪ To include or exclude metadata from all Salesforce Flows metadata, select Flows as the object type and All Types as the filter criteria, and then enter * in the value field.
• ▪ To include or exclude metadata from all Salesforce Data 360 data model objects with names that start with 'Individual', along with the metadata from the associated data model mappings, select Data 360 as the object type, and Data Model Object as the filter criteria, and then enter Individual* in the value field.
6. fOptionally, to define an additional filter with an OR condition, click the Add icon.
4Optional. In the Configuration Parameters area, enter additional settings.
The following table describes the property that you enter for additional settings:
Note:
The
Additional Settings
section appears when you click
Show Advanced
.

Property	Description
Expert Parameters	Enter additional configuration options to be passed at runtime. Required if you need to troubleshoot the catalog source job. Caution: Use expert parameters when it is recommended by Informatica Global Customer Support.

5Configure additional capabilities for the catalog source by clicking on the tabs.

Configure data profiling and quality

1Click the Data Profiling and Quality tab.
2Expand Data Profiling and select Enable Data Profiling.
3In the Connection and Runtime area, choose the Secure Agent group where you want to run catalog source jobs.
4Optionally, specify data profiling filters to run the profile on a subset of the metadata that you extract.
1. aSelect Yes to view filter options.
2. bFrom the Include/Exclude list, choose to include or exclude metadata based on the filter parameters.
3. cFrom the Object type list, select Salesforce Object.
4. dEnter a value to specify the object location.
Examples:
• ▪ You extracted metadata from all Salesforce CRM objects and now you want to run a profile on objects that begin with the name, Finance. Select CRM from the Object type option, Salesforce Object from the Filter criteria option, and then enter Finance* in the input field.
• ▪ You extracted metadata from all Salesforce Data 360 Data Lake objects and now you want to run a profile on all objects that begin with the name, Account. Select Data 360 from the Object type option, Data Lake Object from the Filter criteria option, and then enter Account* in the input field.
To include or exclude multiple objects, click the Add icon to add filters with the OR condition.
5In the Parameters area, configure the parameters.

Parameter	Description
Modes of Run	Determines the type of data that you want the data profiling task to collect. Choose one of the following options: - Keep Signatures Only. Collects only aggregate information such as data types, average, standard deviation, and patterns. - Keep Signatures and Values. Collects both signatures and data values.
Profiling Scope	Determines whether you want to run data profiling only on the changes made to the source system or on the entire source system. Choose one of the following options: - Incremental. Includes only source metadata that is changed or updated since the last profile run. - Full. Includes the entire metadata that is extracted based on the filters applied for extraction.
Sampling Type	Determines the sample rows on which you want to run the data profiling task. Choose any of the following options: - All Rows. Runs data profiling on all rows in the metadata. - Limit N Rows. Runs data profiling on a limited number of rows. - Custom Query. Provides an SQL clause to select sample rows to run the data profiling task.
No of rows to limit	Required if you select Limit N Rows in Sampling Type. Specify the number of rows that you want to run the profile on. Default is 1000.
Sampling Query	Required if you select Custom Query in Sampling Type. Specify an SQL clause to select sample rows to run the data profiling task. For example, WHERE Name__c = 'ABC Corporation' The Name__c field name is the name of the Salesforce API.
Salesforce Data 360 Connection	Required if you want to run the data profiling task on Salesforce Data 360 objects. Select the Salesforce Data 360 connection that you created in Administrator.
Maximum Precision of String Fields	The maximum precision value to be used for profiling fields that include the string data type. Default is 50.
Text Qualifier	The character that defines string boundaries. If you select a quote character, profiling ignores delimiters within the quotes. Select a qualifier from the list. Default is Double Quote.

6Expand Data Quality and select Enable Data Quality.
Note:
You can click
Use Data Profiling Parameters
to use the same parameters as in the
Data Profiling
section.
7In the Connection and Runtime area, choose the Secure Agent group where you want to run catalog source jobs.
8In the Parameters area, configure the parameters.

Parameter	Description
Data Quality Rule Automation	Enable the option to automatically create or update rule occurrences for data elements in the catalog source. Choose one of the following options: - Apply on Data Elements linked with Business Dataset. Creates rule occurrences for all data elements that are linked with business data sets in the catalog source. - Apply on all Data Elements. Creates rule occurrences for all data elements in the catalog source.
Data Quality Remediation	Enable the option to specify a flat file connection to store the list of failed rows so that users can remediate poor data quality scores. Choose one of the following options: - No. Doesn't enable the data quality failure ticket option. - Yes. Shows a list of flat file connections where you write failed rows to customer-managed locations.
Data Quality Failure Ticket	Specify whether you want to create data quality failure tickets for poor data quality scores based on the threshold defined for the rule occurrence in Data Governance and Catalog. Choose one of the following options: - No. Doesn't automatically create data quality failure tickets when the data quality scores are poor. - Yes. Automatically creates data quality failure tickets based on the data quality threshold values you define in Data Governance and Catalog, and notifies you when a data quality score is below the threshold. Note: You must configure a workflow event for the data quality failure and enable the event in Metadata Command Center .
Cache Result	Enable the option to generate a cache file in the runtime environment and preview the cached results faster in subsequent data preview runs. Choose one of the following options: - Agent Cache. Stores the results in the runtime environment cache for seven days by default after the first run. - No Cache. Doesn't store the preview results in the cache. You can only view live results.
Run Rule Occurrence Frequency	Specify whether you want to run data quality rules based on the frequency defined for the rule occurrence in Data Governance and Catalog.
Sampling Type	Determines the sample rows on which you want to run the data quality task. Choose one of the following options: - All Rows. Runs data quality on all rows in the metadata. - Limit N Rows. Runs data quality on a limited number of rows. - Custom Query. Provides an SQL clause to select sample rows to run the data quality task.
No of rows to limit	Required if you select Limit N Rows in Sampling Type. Specify the number of rows that you want to run the data quality task on. Default is 1000.
Sampling Query	Required if you select Custom Query in Sampling Type. Specify an SQL clause to select sample rows to run the data quality task. For example, WHERE Name__c = 'ABC Corporation' The Name__c field name is the name of the Salesforce API.
Salesforce Data 360 Connection	Required if you want to run the data quality task on Salesforce Data 360 objects. Select the Salesforce Data 360 connection that you created in Administrator.
Maximum Precision of String Fields	The maximum precision value to be used for fields that include the string data type. Default is 50.
Text Qualifier	The character that defines string boundaries. If you select a quote character, the data quality task ignores delimiters within the quotes. Select a qualifier from the list. Default is Double Quote.

Configure data classification

1Click the Data Classification tab.
2Select Enable Data Classification.
3Choose one or both of the following options:
• - Generated Data Classifications. CLAIRE automatically generates data classifications for the data elements.
• - Data Classification Rules. Choose from predefined or custom data classifications.
1. 1Click Add Data Classification. The Select Data Classifications dialog box appears.

2. 2Select the data classifications that you want to use.
3. 3Click OK.

Configure relationship discovery

• •Import a relationship inference model. For more information about importing a relationship inference model, see Import a relationship inference model.
• •Enable data profiling on the Data Profiling and Quality tab, and select Keep Signatures and Values as the run mode in the Parameters section. These configurations enable you to retain values of the columns in the profiling results and discover relationships.

1Click the Relationship Discovery tab.
2Select Enable Relationship Discovery.
3In the Column Similarity area, select the Relationship Inference Model.
Note:
The relationship inference models that you imported appear in the
Relationship Inference Model
field.
4In the Joinable Tables Relationship area, specify the Containment Score Threshold to identify joinable table relationships within the catalog source. This score is an indicator of the data overlap between any two given columns which determines whether the tables are joinable.
Note:
A higher score means that the objects have more overlapping data and a lower score means lesser overlapping data between the two objects. A containment score threshold lower than 0.4 might result in a large number of false positives.

Configure glossary associations

Note: Salesforce
source systems can contain ambiguous data with technical field names. To generate accurate glossary associations, CLAIRE uses the extracted Label attribute for such technical field names.
2Click the Glossary Association tab.
3Select Enable Glossary Association.
4Select Enable auto-acceptance to automatically accept glossary association recommendations.
5Specify the Confidence Score Threshold for Auto-Acceptance to set a threshold limit based on which the glossary association capability automatically accepts the recommended glossary terms.
Note:
Specify a percentage from 80 to 100. If the score is higher than the specified limit, the glossary association capability automatically assigns a matching glossary term to the data element.
6Select Enable Below-threshold Recommendations to receive glossary association recommendations below the auto-acceptance threshold. If you enable auto-acceptance, you can enable below-threshold recommendations to receive glossary recommendations below the auto-acceptance threshold.
7Specify the Confidence Score Threshold for Recommendations to set a threshold based on which the glossary association capability makes recommendations
If you enable auto-acceptance, specify a percentage from 80 to the selected auto-acceptance threshold. You can accept or reject the recommended glossary terms that fall within this range in Data Governance and Catalog.
If you disable auto-acceptance, specify a percentage from 80 to 100 inclusive.
8Choose to automatically assign business names and descriptions to technical assets. You can then choose to retain existing assignments and only assign business names and descriptions to assets that don't have assignments, or allow overwrite of existing assignments.
By default, existing assignments are retained.
9Optional. Choose to ignore specific parts of data elements when making recommendations. Select Yes and enter prefix and suffix keyword values as needed.
Click Select to enter a keyword. You can enter multiple unique prefix and suffix keywords. Keyword values are case insensitive.
10Optional. Choose specific top-level business glossary assets to associate with technical assets. Selecting a top-level asset selects its child assets as well. Select Top-level Glossary Assets and specify the assets on the Select Assets page.
11Optional. Choose to use abbreviations and synonym definitions from lookup tables for accurate glossary association. Select Yes to enable, and then click Select to upload a lookup table.
12Click Next.
The Associations page appears.