What's new and changed in watsonx.data intelligence

watsonx.data intelligence updates can include new features and fixes. Releases are listed in reverse chronological order so that the latest release is at the beginning of the topic.

You can see a list of the new features for the platform and all of the services at What's new in IBM Software Hub.

Installing or upgrading watsonx.data intelligence

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  • To install watsonx.data intelligence along with the other IBM® Software Hub services, see Installing IBM Software Hub.
  • To upgrade watsonx.data intelligence along with the other IBM Software Hub services, see Upgrading IBM Software Hub.
  • To install or upgrade watsonx.data intelligence independently, see watsonx.data intelligence.
    Remember: All of the IBM Software Hub components associated with an instance of IBM Software Hub must be installed at the same version.

IBM Software Hub Version 5.2.2

A new version of watsonx.data intelligence was released in October 2025 with IBM Software Hub 5.2.2.

Operand version: 2.2.2

This release includes the following changes:

New features
This release of watsonx.data intelligence includes the following features:
Import, enrich, and assess the quality of data from additional data sources
You can now import metadata from DataStax Enterprise data sources, enrich that data, and assess its quality.

In addition, you can now run advanced analysis on data from IBM Db2 Warehouse data sources, create SQL-based assets from those such sources, and write analysis output to tables in IBM Db2 Warehouse.

View all data protection rule connections in relationship explorer
You can now view all items that are connected to data protection rules in the relationship explorer view to better understand how the rules are applied.
Try the new interface for building reporting queries to gather insights into metadata
You can now use the Reporting queries UI to create complex queries about your assets and artifacts without the need to use SQL. You can save your queries and share them with other users.
Create mapping rules for advanced interpretation of OpenLineage events for lineage generation
You can now creating mapping rules to define how your custom technologies are interpreted and then represented in lineage. As a result, more accurate lineage is generated.
Export lineage to PDF and CSV formats by using new output options
You can now export lineage to PDF and CSV files by using new output options. Use the Assets connections option to include all starting assets and connections to unique assets. Use the Lineage paths option to include all unique paths that originate from the starting assets.
Connect to IBM DataStage for IBM Cloud Pak for Data by using the Manta agent
You can now import lineage metadata from IBM DataStage for IBM Cloud Pak for Data by using an external agent.
Delete lineage for multiple data source definitions at the same time
You can now select more than one data source definition and delete the lineage that is associated with these data source definitions. After the deletion process is complete, a notification is displayed, regardless of your current location in the product.
Updates
The following updates were introduced in this release:
  • For data quality rules with external bindings, you can now configure the columns for quality score reporting in the rule subflow stage.
  • You can now capture SQL-based data quality rules in the reporting data mart.
  • Custom properties can now be used to filter the results in global search.
  • When importing reference data sets, you can now append related values without overwriting the existing ones.
  • Asset description can now be up to 3,000 characters long.
  • You can now add any user or user group as an asset member.
  • For CSV import, added fields for schema, physical table, connection name, and connection resource key details. To associate assets with existing connections, provide schema and physical table details.
  • Expand or collapse all asset children in the initial lineage graph view with just one click.
  • Filter data lineage by quality score.
  • Issues where metadata extraction was getting stuck due to cyclic dependencies between extracted objects have now been fixed for IBM DataStage for IBM Cloud Pak for Data connector.
  • Microsoft Power BI (Azure) large reports (over 1GB) are now correctly extracted even if their names contain space characters.
Customer-reported issues fixed in this release
For a list of customer-reported issues that were fixed in this release, see the Fix List for IBM Cloud Pak® for Data on the IBM Support website.
Security issues fixed in this release
The following security issues were fixed in this release:

CVE-2025-1094, CVE-2025-32414, CVE-2025-32415, CVE-2025-3730, CVE-2025-3777, CVE-2025-3933, CVE-2025-41242, CVE-2025-4373, CVE-2025-47273, CVE-2025-48989, CVE-2025-5197, CVE-2025-5222, CVE-2025-52520, CVE-2025-53506, CVE-2025-53864, CVE-2025-55163, CVE-2025-5914, CVE-2025-6965, CVE-2025-7425, CVE-2025-8058, CVE-2025-8194, CVE-2025-8714, CVE-2025-8715, CVE-2025-8916, CVE-2025-8941

CVE-2024-0397, CVE-2024-0985, CVE-2024-10979, CVE-2024-13009, CVE-2024-28863, CVE-2024-35195, CVE-2024-3651, CVE-2024-37891, CVE-2024-4317, CVE-2024-47081, CVE-2024-52533, CVE-2024-7143, CVE-2024-7348, CVE-2024-7592

CVE-2023-2727, CVE-2023-2728, CVE-2023-39417, CVE-2023-39418, CVE-2023-43804, CVE-2023-5868, CVE-2023-5869, CVE-2023-5870

CVE-2022-29458, CVE-2022-3606, CVE-2022-3857

CVE-2021-41720, CVE-2021-45940, CVE-2021-45941

IBM Software Hub Version 5.2.1

A new version of watsonx.data intelligence was released in August 2025 with IBM Software Hub 5.2.1.

Operand version: 2.2.1

This release includes the following changes:

New features
This release of watsonx.data intelligence includes the following features:
Relationship explorer shows all SLA rules and reference data sets relationships
The Relationship explorer now shows more relationships:
  • All items that are connected to SLA rules are displayed.
  • Relationships between reference data values in the same or various reference data sets are displayed. One-to-one and one-to-many relationships are shown. 
These enhanced relationship visualizations provide a more complete governance view and improve impact analysis and compliance tracking.
Select models for use with the gen AI capabilities
If your deployment is set up to run the models for the gen AI capabilities on a remote instance of watsonx.ai™, you can now choose to work with other supported foundation models instead of the default ones. 
Use definition-based data quality rules with external bindings multiple times in your DataStage flows
Tech preview You can now create data quality rules that you can use any number of times in one or more DataStage flows. Create a definition-based rule with external bindings in the project. Then, add the rule to a DataStage flow by selecting it from the Asset Browser stage as many times as needed. When you update the respective data quality rule asset, the changes are automatically reflected in any flow that contains the rule. For each rule that you run, you can decide which associated DataStage flows are run.
Import sample predefined business terms with the Knowledge Accelerators UI

You can now install a sample of 100 predefined business terms by using the Knowledge Accelerators importing UI. Use the sample business terms to classify personal data across key concepts such as Person, Organization, Employment Record, Contact Information, and Finance Information.

Customize lineage visualization with enhanced filters

You can now adjust the initial view of your lineage by using advanced filters. Decide on the scope of data and type of assets that you want to see on your lineage.

Connect to new data sources by using the Manta agent

You can now import lineage metadata from the following data sources by using an agent:

  • Amazon RDS for PostgreSQL
  • Amazon Redshift
  • Greenplum
  • IBM Cloud Databases for PostgreSQL
  • PostgreSQL

You can install a Manta agent on a system with direct access to a data source if connecting directly from IBM Cloud Pak for Data is not possible.

Connect to Google BigQuery with Workload Identity Federation authentication methods

When you import lineage metadata from a Google BigQuery data source, you can now use a connection with these authentication methods:

  • Workload Identity Federation with an access token

  • Workload Identity Federation with a token URL.

These methods are used when authentication is solved by an external service.

New data sources for lineage metadata import
You can now import lineage metadata from the following additional data sources:
  • Qlik Sense
  • Teradata

After the data is imported, you can visualize it on a lineage graph.

Manta agents can now be used in FIPS-enabled clusters

You can now use external Manta agents to import lineage metadata from FIPS-enabled environments.

Create text queries to SQL queries in projects
You can now add SQL assets to your projects by converting your text query to SQL.
Use data lineage to track data and visualize the flow of data

Data providers can now use data lineage to track and visualize the complete flow of data from its origin, through each transformation, to its final use. Data lineage provides end-to-end transparency so that providers can track how data assets evolve and perform faster root cause analysis for data quality issues.

Semantic search enhancements for your data product search

Global search for data products is now integrated with the semantic search service. Semantic search enhances search accuracy by understanding the context and intent behind search terms, rather than just matching keywords. You can search text in the query to provide relevant search results. For example, if you search "automobile", the data products search will automatically be expanded to return similar terms, such as the word "car".

Updates
The following updates were introduced in this release:
  • For new projects, the default method for generating display names in metadata enrichment is now Generative AI.
  • You can now select assets or columns from multiple pages for bulk actions in metadata enrichment.
  • You can now run data quality rules on data from Salesforce.com data sources and create query-based data assets from such data sources.
  • The Data Quality feature is now also available on Power (ppc64le) hardware.
  • When you're creating metadata imports for discovery and lineage, you can now edit your goals after the job is completed. If you can't use a goal with the selected DSD or connection, the goal isn’t available on the Define goals page.
  • Custom properties and relationships can now be restricted by categories.
  • Text is now set as default when creating a new reference set.
  • When bulk-editing categories, you can now make edits to collaborators.
  • Column-level lineage has been enhanced so that it is easier to follow the flow of data.
  • When you view lineage for PostgreSQL assets, you can view the source code of the transformation asset to check the details of the transformation logic.
  • MicroStrategy reports and dossiers that have prompts are now displayed on lineage.
  • Lineage is now created for OpenLineage events that do not have input metadata defined, but have output and job metadata.
Customer-reported issues fixed in this release
For a list of customer-reported issues that were fixed in this release, see the Fix List for IBM Cloud Pak for Data on the IBM Support website.
Security issues fixed in this release
The following security issues were fixed in this release:

CVE-2025-0938, CVE-2025-22227, CVE-2025-22233, CVE-2025-22235, CVE-2025-22868, CVE-2025-22869, CVE-2025-22870, CVE-2025-22871, CVE-2025-22872, CVE-2025-23165, CVE-2025-23166, CVE-2025-23167, CVE-2025-24528, CVE-2025-24928, CVE-2025-24970, CVE-2025-25193, CVE-2025-25724, CVE-2025-27144, CVE-2025-2953, CVE-2025-30749, CVE-2025-30754, CVE-2025-30761, CVE-2025-31498, CVE-2025-32462, CVE-2025-3262, CVE-2025-3263, CVE-2025-3264, CVE-2025-3277, CVE-2025-3576, CVE-2025-41234, CVE-2025-4138, CVE-2025-4330, CVE-2025-4435, CVE-2025-4517, CVE-2025-46653, CVE-2025-46701, CVE-2025-4673, CVE-2025-46762, CVE-2025-47287, CVE-2025-4802, CVE-2025-48060, CVE-2025-48379, CVE-2025-48734, CVE-2025-48988, CVE-2025-49124, CVE-2025-49125, CVE-2025-49794, CVE-2025-49796, CVE-2025-50106, CVE-2025-53643, CVE-2025-54121, CVE-2025-5702, CVE-2025-6020, CVE-2025-6021, CVE-2025-6545, CVE-2025-6547, CVE-2025-7339, CVE-2025-7783

CVE-2024-10963, CVE-2024-12087, CVE-2024-12088, CVE-2024-12133, CVE-2024-12243, CVE-2024-12718, CVE-2024-12747, CVE-2024-22201, CVE-2024-23337, CVE-2024-23944, CVE-2024-40635, CVE-2024-52615, CVE-2024-56171, CVE-2024-8184, CVE-2024-9823

CVE-2023-24056, CVE-2023-2976, CVE-2023-43642, CVE-2023-44981

CVE-2022-25647, CVE-2022-49043

CVE-2020-11022, CVE-2020-11023, CVE-2020-23064, CVE-2020-7656, CVE-2020-8908

CVE-2019-11358, CVE-2019-5428

CVE-2018-10237

CVE-2015-9251

CVE-2014-6071

CVE-2012-6708

CVE-2011-4969

IBM Software Hub Version 5.2.0

IBM watsonx.data intelligence is a new service that is available on IBM Software Hub.

Watsonx.data intelligence was released in June 2025 with IBM Software Hub 5.2.0.

Operand version: 2.2.0

IBM watsonx.data intelligence delivers all the tools that you need to:
  • Deliver trusted, high-quality data
  • Visualize the end-to-end flow of data
  • Share data across your entire organization
Data governance and catalog
Effective data governance is crucial for maintaining data integrity, privacy, and security. With the data governance solutions that watsonx.data intelligence provides, you can establish policies and procedures for managing your structured and unstructured data. These tools help enforce compliance with regulatory requirements like GDPR and CCPA, manage metadata, and track data usage across the organization. By implementing a robust data governance framework, you can ensure that your data is handled responsibly and ethically.
Data quality
Watsonx.data intelligence provides robust solutions to enhance data quality. These tools help you ensure that your data is accurate, consistent, and trustworthy. By implementing data quality best practices, you can improve the reliability of your analytics, leading to better decision-making. The data quality tools include automated data profiling, cleansing, and validation capabilities that help you to identify and rectify data issues promptly.
Data lineage
Understanding the origin and transformation of data is essential for maintaining data quality and compliance. The data lineage tools in watsonx.data intelligence provide detailed insights into the data lifecycle, showing how data moves and changes over time. This transparency is critical for auditing purposes and quickly helps you identify the source of data issues. Data lineage capabilities also support impact analysis, which helps you to understand the potential effects of changes to data processes.
Data Product Hub
Watsonx.data intelligence facilitates secure and efficient data sharing within and outside of your organization. The data sharing tools make the right data accessible to the right people while protecting sensitive information. You can streamline data sharing with automated delivery of data products to data consumers across the organization. By using the data sharing tools, you can break down silos by connecting to disparate source systems to simplify the onboarding of reusable data products, no matter where the data resides. You also gain data lifecycle management capabilities to manage data-as-a-product and cost-effectively deliver fit-for-purpose data and analytics products to data consumers. By promoting a culture of data sharing, you can foster collaboration, drive innovation, and accelerate decision-making in your organization.