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 tabs and asset pages
- Manually assign semantic types to fields
- View score trends
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Support for Microsoft Azure Data Lake Storage
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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 streamlines navigation, reduces menu clicks, and provides quick access to business context and downstream dependencies. | View business assets related to a technical asset Manage relationships between technical and business assets | Available to all |
| Catalog | Search Catalog from secondary tabs and asset pages |
Access the search bar from any Catalog asset detail page and secondary tabs, 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. |
Search from secondary tabs and asset pages | Available to all |
| 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. | Available to all | |
| 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 | Available to all |
| 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 Notebook | Available to all |
| 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’s 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 section, 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 help ensure secure, controlled, and auditable API usage across your organization. |
Service users | Coming soon |
| 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. | View data integration usage metrics | Coming soon |
| 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. | View data quality usage metrics | Coming soon |
| 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 and ensures that pipelines process only relevant records identified by existing Quality Rules. | Upload sample data for pipeline preview and configuration | Coming soon |