The April 2025 release of Data Governance and Catalog includes the following changed behaviors.
Edit primary data element in a data quality rule occurrence
After you create a data quality rule occurrence in Data Governance and Catalog, you can edit the primary data element only if the new primary data element belongs to the same catalog source as the previous one. You cannot edit the primary data element after you have run the rule occurrence. Note that you can edit the primary data element of the rule occurrence in Data Governance and Catalog only. You can perform this action only through the user interface.
Previously, you could only add the primary data element while creating a rule occurrence.
Select rule specifications with multiple outputs in technical rule reference
When you create a data quality rule occurrence or a data quality rule template, you can use the Technical Rule Reference field to select rule specifications that have multiple outputs.
Previously, the rule specification that you selected could have only one additional output other than the available exception task outputs.
Renamed the Rule Port Name column in the bulk import template
The Rule Port Name column in the data quality rule template and a data quality rule occurrence bulk import template is renamed to Input Port Name.
View upstream and downstream assets on the Hierarchy tab
On the Hierarchy tab of an asset, you can now view both the upstream and downstream assets.
Previously, the Hierarchy tab displayed only the child assets of the open assets.
Addition of data element sensitivity icon
You can now see the sensitivity icon for each data element individually, if they have a data sensitivity level set. You can view the sensitivity icons for data elements in the Data Classification section, Contains tab, asset Overview page, and asset preview panel.
Relationship search and export improvement
You can now view and export all the search results when searching for assets.
Previously, you could export a maximum of 2000 assets for relationship-based search queries, and a maximum of 10,000 assets for other search queries.
Enhancements to removing asset relationships
On the Relationships tab of an asset, the Delete icon is now replaced with the Remove Relationship icon. Additionally, the Remove Relationship icon is displayed perpetually unlike the Delete icon that was displayed only when you hovered over a relationship.
The following image displays the Remove Relationship icon on the grid view of the Relationships tab of an asset page:
Display only accepted recommendations as related assets
You can now view the glossary and data classification recommendations for the asset only if you are a stakeholder of the asset. If you are not a stakeholder of the asset, you can view only the glossary and data classification recommendations that are accepted for the asset.
Furthermore, Data Governance and Catalog now displays the CLAIRE Recommendation icon and a dotted line to indicate the glossaries and data classifications that are recommended for an asset. You can view this icon on the following pages:
•The Relationships tab of an asset.
•The Lineage tab of an asset.
•The Related Assets tab in the Preview Pane for an asset.
Previously, you could view all the glossries and data classifications that are recommended for the asset even if you were not a stakeholder of the asset.
Predefined workflows
Predefined workflows are now available in Metadata Command Center.
Previously, you had to download and import predefined bundles from Administrator as processes to Application Integration.
You can now schedule organization upgrades of Metadata Command Center, Data Governance and Catalog, and Data Marketplace after Informatica makes the version available on the POD that you connect to.
Previously, you could not schedule organization upgrades.
To initiate the organization upgrade, you must now be the organization administrator or have the Manage Upgrade privilege for your user role. If you don't initiate the upgrade, Informatica upgrades your organization six weeks after it makes the version available on the POD.
Previously, to initiate the upgrade, you had to be the organization administrator or have the Super Admin privilege for your user role.
For more information about feature privileges that are available for Metadata Command Center in Administrator, see Feature privileges in Administrator.
Snowflake metadata extraction method
Metadata Command Center can now also use information_schema.tables, information_schema.views, and information_schema.columns to extract metadata from Snowflake catalog source.
Previously, Metadata Command Center only used show commands.
Extract pipeline instances from Microsoft Azure Data Factory source systems
When you extract metadata, unique pipeline instances get extracted by default and the pipeline instance name is followed by a hash. The pipeline runid is not appended to the name. You can view the pipeline runid as a property of the pipeline instance that was previously extracted.
Previously, you had to enable the operational metadata option to extract pipeline instances. The pipeline runid was appended to the pipeline instance name.
The following catalog source types have been renamed:
Previous name
Current name
Microsoft Azure Synapse
Microsoft Azure Synapse Data Warehouse
Microsoft Azure Synapse Script
Microsoft Azure Synapse Data Warehouse Script
Rerun the connection assignment job
You can rerun the connection assignment job to resolve any failures that occurred during connection assignment. When you rerun the connection assignment job, the job reassigns the existing endpoint objects to the selected connection.
Previously, you had to rerun the catalog source to resolve any connection assignment failures.
For more information about connection assignment, see Connections.
Random N Percentage Sampling Type for data profiling on Google BigQuery
The Random N Percentage sampling type for data profiling task uses the TABLESAMPLE clause to select random subsets of data. It selects data based on the percentage that you specify in the Percentage of data to select field.
Previously, the sampling type query selected all rows from the table.
When you choose the Random N Percentage sampling type, you can run data profiles on the following objects:
•Table
•External Table
Note: You can run data profiles only on external tables that are created in Google Cloud Storage.
