Data governance guide

This guide shows how to manage data and data access in Azure Databricks. For information on Azure Databricks security, see the Security guide. The Databricks Security and Trust Center also provides information about the ways in which security is built into every layer of the Databricks Lakehouse Platform.

  • Unity Catalog is a fine-grained governance solution for data and AI on the Lakehouse. It helps simplify security and governance of your data by providing a central place to administer and audit data access.
  • Data Explorer is a data discovery UI you can use to explore and manage data, schemas (databases), tables, and permissions.
  • Hive metastore table access control (legacy) lets you apply data governance controls to your data.
  • Credential passthrough (legacy) allows you to authenticate automatically to Azure Data Lake Storage from Azure Databricks clusters using the identity that you use to log in to Azure Databricks.
  • Audit logs allow your enterprise to monitor details about usage patterns across your Databricks account and workspaces.

To learn the best practices for data governance in Azure Databricks, see Data governance best practices.

For information on Azure Databricks security, see Databricks Security and Trust Center, which provides information about the ways in which security is built into every layer of the Databricks Lakehouse Platform.

In this guide: