Microsoft Fabric Data Warehouse Sources > Create catalog sources in Metadata Command Center > Step 2. Configure capabilities
  

Step 2. Configure capabilities

When you configure the Microsoft Fabric Data Warehouse catalog source, you define the settings for the metadata extraction capability and other optional capabilities.
The metadata extraction capability extracts source metadata from external source systems. You can also configure other capabilities that the catalog source includes.
You can save the catalog source configuration at any point after you enter the connection information. After you save the catalog source, you can choose to run the catalog source job. To run the job once, click Run. To run metadata extraction and other capabilities on a recurring schedule, configure schedules on the Schedule tab.

Configure metadata extraction

When you configure a Microsoft Fabric Data Warehouse catalog source, you choose a runtime environment, define filters, and enter configuration parameters for metadata extraction.
Before you configure metadata extraction, configure runtime environments in the IDMC Administrator.
    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.
    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:
    To define filters, you can either select an object type and enter the path to the object as the filter value, or select an object from a list of objects available in the source system.
    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. cPerform one of the following steps:
    4. Filters can contain the following wildcards:
      For object hierarchies, use a dot as a separator.
      When you enter values for filters, enclose them in double quotes if you use a space or a dot in a single segment.
      The following image shows the filter condition options:The image shows the filter conditions with the Search button.
      Examples:
    5. dOptionally, to define an additional filter with an OR condition, click the Add icon.
    4Optionally, in the Configuration Parameters area, enter properties to override default context values and job parameters.
    Note:
    Click
    Show Advanced
    to view all configuration parameters.
    The following table describes the properties that you enter for Catalog Source Configuration Options:
    Parameter
    Description
    Default variables values
    Specify a default value for variables used in the programmable objects.
    MetaTables Include Filter
    Advanced parameter. When you process PL/SQL statements, Metadata Command Center does not read tables or view content by default. If you want to use the content, for example, to process dynamic SQL statements, use the MetaTables Include Filter parameter. This parameter prompts the database for the required metadata. Verify that the user has SELECT permissions for metatables.
    Note:
    Don't use this option to specify filters for tables that you want to include or exclude during the metadata extraction run.
    The following table describes the property that you can 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 lineage discovery

Enable the lineage discovery capability and use CLAIRE to build complete lineage by recommending endpoint catalog source objects to assign to reference catalog source connections.
    1Click the Lineage Discovery tab.
    2Select Enable Lineage Discovery.
    3In the Filters area, define one or more filter conditions to apply for lineage discovery.
    To define filters, you can choose to select catalog source types, asset groups, or enter a catalog source name or search from a list of catalog sources.
    1. aSelect Yes to view filter options.
    2. bFrom the Include/Exclude list, choose to include or exclude catalog sources for lineage discovery based on the filter parameters.
    3. cFrom the filter type list, select catalog source type, catalog source name, or asset group.
    4. dIn the filter value field, select the required catalog source types, or click the Search button and select catalog sources or asset groups.
    5. Filters can contain the asterisk wildcard to represent multiple characters or empty text.
      The filter options appear.The filter options include multiple filter conditions that you can choose.
      Examples:
      Note:
      You can't add more than one include or exclude filter for the same filter type.
    6. eOptionally, to define an additional filter with an AND condition, click the Add icon.
    7. For more information about lineage discovery, see Lineage discovery.

Configure data profiling and quality

Enable the data profiling capability to evaluate the quality of metadata extracted from the Microsoft Fabric Data Warehouse source system.
    1Click the Data Profiling and Quality tab.
    2Expand Data Profiling and select Enable Data Profiling.
    Note:
    Ensure that you have permissions on all the staging connections that you use in your data profiling configuration. You can't run the job if you don't have permissions on the connections that you use. Select connections that you have access to, or ask the administrator to grant the necessary permissions on the connections that you want to use.
    3Optional. In the Filters area, specify additional filters in addition to metadata filters:
    1. aSelect Yes to view filter options.
    2. bFrom the Include or Exclude metadata list, choose to include or exclude metadata based on the filter parameters.
    3. cFrom the object type list, select Tables or Views depending on the object that you want to extract metadata from. Select All to extract metadata from all objects in the schema.
    4. dEnter the path to the object as the filter value.
    5. Examples:
      To include or exclude multiple objects, click the Add icon to add filters with the OR condition.
    4In the Parameters area, configure the following parameters based on your requirements:
    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 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.
    • For example, where column1='X'; TABLESAMPLE(X ROWS); TABLESAMPLE(X PERCENT)
    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.
    Maximum Precision of String Fields
    The maximum precision set for profiling fields of the string data type.
    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.
    5Expand 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.
    Note:
    Ensure that you have permissions on all the staging and flat file connections that you use in your data quality configuration. You can't run the job if you don't have permissions on the connections that you use. Select connections that you have access to, or ask the administrator to grant the necessary permissions on the connections that you want to use.
    6In the Parameters area, configure the following parameters based on your requirements:
    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.
    Cache Result
    Select Agent Cache if you want to generate a cache file in the runtime environment and to preview the cached results faster in subsequent data preview runs. The results are cached for seven days by default after the first run in the runtime environment. Select No Cache if you don't want to cache the preview results and view the 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 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.
    • For example, where column1='X'; TABLESAMPLE(X ROWS); TABLESAMPLE(X PERCENT)
    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.
    Maximum Precision of String Fields
    The maximum precision set for profiling fields of the string data type.
    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.
    7To enable the data observability capability, expand Data Observability and select Enable Data Observability.

Configure data classification

Enable the data classification capability to identify and organize data into relevant categories based on the functional meaning of the data.
    1Click the Data Classification tab.
    2Select Enable Data Classification.
    3Choose one or both of the following options:

Configure relationship discovery

Enable the relationship discovery capability to identify pairs of similar columns and relationships between tables within a catalog source.
Before you configure relationship discovery, perform the following tasks:
    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.
After you run the catalog source job, you can view the inferred relationships on the Relationships tab of the extracted assets in Data Governance and Catalog.

Configure glossary associations

Enable the glossary association capability to associate glossary terms with technical assets, or to get recommendations for glossary terms that you can manually associate with technical assets in Data Governance and Catalog.
Metadata Command Center considers all published business terms in the glossary while making recommendations to associate your technical assets.
    1Click the Glossary Association tab.
    2Select Enable Glossary Association.
    3Select Enable auto-acceptance to automatically accept glossary association recommendations.
    4Specify 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.
    5Select 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.
    6Specify 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.
    7Choose 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.
    8Optional. 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.
    9Optional. 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.
    10Optional. 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.
    11Click Next.
    The Associations page appears.