Data governance guide
This guide shows how to manage data and data access in Databricks. For information on Databricks security, see the Security and compliance 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. You deploy compute resources with instance profiles for secure access to data stored in S3. You then use table access control for fine-grained permissions to the data.
Credential passthrough (legacy) allows you to authenticate automatically to S3 buckets from Databricks clusters using the identity that you use to log in to 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 Databricks, see Data governance best practices.
For information on 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: