What's new and changed in IBM Knowledge Catalog

IBM Cloud Pak for Data Version 5.2.0

A new version of IBM Knowledge Catalog was released in June 2025.

This release includes the following changes:

New features

This release of IBM Knowledge Catalog, IBM Knowledge Catalog Premium, and IBM Knowledge Catalog Standard includes the following features:

IBM Knowledge Catalog is now available on Power hardware

You can now install the IBM Knowledge Catalog service on a Red Hat® OpenShift® Container Platform on Power (ppc64le) hardware.

Manage identical data assets consistently

Govern connected data assets that represent the same physical resource (identical data assets) across multiple governed catalogs and specific projects. Now, connected data assets reference the same set of asset properties (shared properties), so when shared properties and their values are updated, the changes are immediately visible on all identical data assets across the specified workspaces. 

For details, see Identical data assets.

Generate business terms with gen AI-powered glossary generation

In IBM Knowledge Catalog Premium, facilitate data governance by automatically generating business terms and reducing the time that is needed to establish glossaries. Business terms are generated based on specific business need. Business terms have defined names and descriptions. The terms are already linked to specific data with automatically assigned relationships to other business terms in the glossary.

For details, see Generating business terms.

Publish SQL query assets to catalogs

You can now publish SQL query asset types to catalogs. In governed catalogs, previews of SQL query data assets with data protection rules enforced are also available.

For details, see Publishing assets from a project into a catalog .

Define execution windows for metadata import jobs

With execution windows, you can set your metadata import jobs to run only in the specified time ranges on selected days as needed. Your job runs will pause automatically if not complete within the configured execution window, and the jobs will resume when the next execution window starts.

For details, see Managing existing metadata imports in a project.

Enhanced setup options for gen AI capabilities

You can now enable the generative AI capabilities in IBM Knowledge Catalog Premium with one of these model options:

• Use a Granite model that is started on the internal containers with CPUs for LLM-based enrichment.
• Use local watsonx.ai™ inference foundation models (watsonx_ai_ifm) that require GPU for LLM-based enrichment, and term generation and assignment.
• Work with external watsonx.ai models in an existing IBM watsonx.ai instance on a remote IBM Cloud Pak® for Datacluster or in IBM watsonx™ as a Service for LLM-based enrichment, and term generation and assignment.

For details, see Specifying installation options in the IBM® Software Hub documentation.

Automate data quality analysis

Instead of running a basic data quality analysis with a fixed set of predefined checks in metadata enrichment, you can now have data quality checks automatically generated for your data. You can immediately run these suggested checks as another step in the enrichment . Or, you can review and adjust the checks, and then add the run step to the enrichment before you re-enrich your data.

Data quality checks can be generated based on profiling results, generated based on constraints that are defined in assigned business terms, or you can manually add them to check an entire data asset or specific columns. Users can decide whether these checks should be applied without further review, or review and then have the reviewed ones applied. Available types of data quality checks include the checks that were available in earlier releases and a set of new checks, for example, checks for historical stability and referential integrity.

For details, see:

• Designing metadata enrichment
• Available types of data quality checks

Provide additional context for name generation in metadata enrichment

In IBM Knowledge Catalog Premium, you can now configure default enrichment settings to provide additional context to the model when you run metadata enrichment with the option to generate display names by using generative AI:

• Use data from the sample that is generated by profiling
• Use a custom set of abbreviations
• Use assets with assigned display names

For details, see Expand metadata in Metadata enrichment default setting.

Rule-based term assignment

You can now set up rules and rule groups for how you want terms to be assigned to data assets and columns. Upload the rules to a project as a CSV file for consumption by the term assignment service.

For details, see Rule-based term assignment in Default enrichment settings.

Import, enrich, and assess data quality of data from additional data sources

You can now import metadata from remote file systems by using an FTP connection, enrich that data, and assess its quality.

For details, see Supported data sources for curation and data quality.

Add governance artifacts with View permission on the target

You can now create a custom relationship type for governance artifacts that have only a Viewer permission on the target of the relationship. If you create this kind of relationship type, more people within the organization will be able to create necessary relationships.

For more information, see Custom properties, relationships, and asset types.

View indirect relationships on the relationship explorer canvas

You can now see indirect relationships between items on the canvas. Indirect relationship appears when some items were hidden on the canvas and other items connects through them. Those relationships are indicated by a dashed line.

For more information, see Exploring relationships.

Use AI search to find assets and artifacts

The search experience is enhanced with LLM-based technology. You can now use AI search when searching for artifacts and assets. By extracting and rewriting your search queries with semantically equivalent terms, intelligent search provides more relevant and comprehensive results, even if your exact words are not present in the indexed content. Such results are marked with the AI icon. With AI search you can navigate through complex data catalogs effortlessly, improving data discovery by surfacing assets that would otherwise remain hidden due to mismatched terminology.

For more information, see Searching for assets.

Import Knowledge Accelerators with the new user interface

You can now import Knowledge Accelerators with the end-to-end setup interface offering a guided experience that requires no advanced technical skills. The import tool simplifies installation, so you can quickly adopt Knowledge Accelerators and drive value from data governance tools.

For more information, see Getting started.

Updates

The following updates were introduced in this release:

• Accept or reject the display names or descriptions that are generated for data assets and columns in bulk from the metadata enrichment results (IBM Knowledge Catalog Premium).
• Data quality SLA assessments are now also run when the data quality score of an asset changes as the result of running a data quality rule. An instance administrator can disable data quality SLA assessments for results of rule runs for the entire deployment.
• The Knowledge Accelerators Data Privacy content has been updated to include new classified business terms in areas of Social Media, Biometrics and Location tracking. The existing classifications to guide the identification of personal information (PI) and sensitive personal information (SPI) have also been updated.
• The following reporting enhancements were introduced:
  • Include custom properties outside of a property group
  • Include custom properties scoped to catalog and project