Data Quality API for Unified Catalog (Public Preview)

If you use the Microsoft Purview Unified Catalog Data Quality service, you can automate data quality management configurations using the Data Quality API. The Data Quality API allows you to programmatically interact with data quality rules, measure data quality, and retrieve data quality scores for your data assets. You can use the API to perform the following tasks:

• Set up data source connections required for running data quality checks.
• Create and manage data quality rules.
• Profile data to understand distribution, completeness, uniqueness, and other statistical metrics.
• Run data quality assessments by applying rules to data assets.
• Access and consume data quality scores.

The initial set of APIs are available in Public Preview starting December 2025. This release includes API coverage for Data Quality features that are Generally Available (GA) only. APIs are not available for Data Quality alerting, schema import, and all features that are currently in Preview.

To begin using these APIs, start by learning how to authenticate. For more information, see Authenticate and call the APIs (tutorial) and Microsoft Purview Data Quality APIs.

Data Quality Lifecycle

If you're new to data quality, perform the following steps to set up and monitor data quality in your tenant:

1. Assign users data quality steward permissions in Unified Catalog to use all data quality features. For more information, see How to assign catalog level roles.
2. Register and scan a data source in Microsoft Purview Data Map. For more information, see Register a new source and Scan data sources in Data Map.
3. Add your data asset to a data product. For more information, see Add and remove data assets.
4. Set up a data source connection to prepare your source for data quality assessment. For more information, see Set up data source connection for data quality in Unified Catalog.
5. Configure and run data profiling for an asset in your data source. When profiling is complete, browse the results for each column in the data asset to understand your data's current structure and state. For more information, see Configure and run data profiling for a data asset.
6. Set up data quality rules based on the profiling results, and apply them to your data asset. For more information, see Create data quality rules.
7. Configure and run a data quality scan on a data product to assess the quality of all supported assets in the data product. For more information, see Configure and run a data quality scan.
8. Review your scan results to evaluate your data product's current data quality. For more information, see Review data quality scores of data assets.
9. Repeat steps 5-8 periodically over your data asset's lifecycle to ensure it's maintaining quality.
10. Continually monitor your data quality to resolve data quality problems or set up data quality notifications to alert you to issues. For more information, see Data quality improvement actions and Set up data quality alerts.

See Also

To learn about the Microsoft Purview APIs for Data Security solutions, see Overview of Microsoft Purview API in Microsoft Graph.

To learn about Data Governance, see Data Governance with Microsoft Purview.

To learn about what's new in Microsoft Purview, see What's new in Microsoft Purview.