This topic describes the enhancements and modifications included in the March 2026 releases of Data Integrity Suite.
- View related business terms for a technical asset​
- Search Catalog from secondary pages and asset pages
- Manually assign semantic types to fields
- View score trends​
-
Support for Microsoft Azure Data Lake Storage
-
Migrated SAP to common data connections​
Link to the video: What's new video - March 2026
| Service | Feature | Description | Documentation | Availability status |
|---|---|---|---|---|
| Catalog | View related business terms for a technical asset | Access business context without leaving the asset page. When
reviewing a technical asset, you can now view all related business
assets directly in the technical asset's details view. Select any
related business asset to go to it instantly. This enhancement
simplifies navigation, reduces menu selections, and provides quick access
to business context and downstream dependencies.
This feature is also available in Government workspaces. |
Manage technical asset relationships Manage technical asset relationships | Public |
| Catalog | Search Catalog from secondary pages and asset pages |
Access the search bar from any Catalog asset detail page and secondary pages, including Details, Lineage, Profile, Relationships, Rules, Scoring, Assignments, Sample, and Change History. Search Technical Assets or Business Assets without interrupting your workflow. The search experience remains consistent with the Catalog landing page, providing access to recent searches and recently accessed assets. Filters and search preferences are retained when navigating results. This feature is also available in Government workspaces. |
Search and sort assets | Public |
| Catalog | Score trends | Scoring trends give you a visual, time based view of how Data Quality
and Data Governance scores change over time, helping you monitor rule
performance beyond point-in-time evaluations. This enhancement enables
you to identify patterns, detect deviations from expected behavior, and
analyze historical score progression across selectable time periods,
including rollup scores for aggregated assets. Scoring trends are
available wherever scores are generated across the Catalog, Quality, and
Governance experiences and present interactive graphs that allow you to
filter by time range, view precise score details, and take informed
action to refine rules and address issues efficiently.
This feature is also available in Government workspaces. |
Public | |
| Configuration | Support for Microsoft Azure Data Lake Storage (ADLS) | The Microsoft Azure Data Lake Storage (ADLS) connector enables organizations to establish secure, authenticated connections to their ADLS accounts and discover data assets for cataloging and lineage tracking. This connector supports both Service Principal and Azure Key Vault authentication methods, providing flexible security options for enterprise deployment. | Azure Data Lake Storage (ADLS) Gen2 | Public |
| Configuration | Support for Databricks Notebook |
Added support for Databricks Notebook datasource, enabling seamless data cataloging and lineage. Also, enhanced security with key vault integration for credential management. |
Databricks | Public |
| Configuration | Service users | Service users introduce a secure and
scalable approach to managing API access by
replacing personal credentials with dedicated
accounts. This enhancement strengthens your
organization security posture by enabling granular
permission control, enforcing least-privilege
access, and providing full audit visibility for all
API interactions. You can now create service users from the Security page, assign user groups to define permissions, and generate up to two API keys per account to support seamless key rotation without disrupting integrations. These capabilities provide secure, controlled, and auditable API usage across your organization. |
Set up service accounts | Preview |
| Integration | Data Integration usage metrics | The Data Integration consumption monitor provides metrics on the volume of data transferred through your replication projects and pipelines. This helps you track your data usage and manage resources more efficiently. Data is measured in bytes, indicating the total amount replicated or applied in your workspace, and this metric covers all continuous and mainframe replication projects. | Track service consumption | Preview |
| Quality | Data Quality usage metrics | The Data Quality usage page displays the amount of data processed by both Data Quality rules and Data Quality pipelines in relation to your available quota. This allows you to monitor your data usage, anticipate future capacity requirements, and analyze your usage trends. | Track service consumption | Preview |
| Quality | Pipeline input with independent samples and Quality rule-based executions | Facilitate faster and more flexible pipeline design and execution by enabling the upload of standalone sample files for pipeline creation and testing, and by allowing pipeline runs to use a SQL-based Quality Rule as the input source. This approach simplifies pipeline design by removing the need to onboard data so that pipelines process only relevant records identified by existing Quality Rules. | Validate and run quality pipelines | Preview |