Events
Mar 31, 11 PM - Apr 2, 11 PM
The ultimate Microsoft Fabric, Power BI, SQL, and AI community-led event. March 31 to April 2, 2025.
Register todayThis browser is no longer supported.
Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support.
This guide shows how to manage data and AI object access in Azure Databricks. For information on Azure Databricks security, see the Security guide. Azure Databricks provides centralized governance for data and AI with Unity Catalog and Delta Sharing.
Unity Catalog is a fine-grained governance solution for data and AI on the Databricks platform. It helps simplify security and governance of your data and AI assets by providing a central place to administer and audit access to data and AI assets.
In most accounts, Unity Catalog is enabled by default when you create a workspace. For details, see Automatic enablement of Unity Catalog.
For a discussion of how to use Unity Catalog effectively, see Unity Catalog best practices.
You can use Unity Catalog to capture runtime data lineage across queries in any language executed on an Azure Databricks cluster or SQL warehouse. Lineage is captured down to the column level, and includes notebooks, jobs, and dashboards related to the query. To learn more, see Capture and view data lineage using Unity Catalog.
Databricks Catalog Explorer provides a UI to explore and manage data and AI assets, including schemas (databases), tables, volumes (non-tabular data), and registered ML models, along with asset permissions, data owners, external locations, and credentials. You can use the Insights tab in Catalog Explorer to view the most frequent recent queries and users of any table registered in Unity Catalog.
Delta Sharing is an open protocol developed by Databricks for secure data and AI asset sharing with other organizations, or with other teams within your organization, regardless of which computing platforms they use.
Databricks provides access to audit logs of activities performed by Databricks users, allowing your enterprise to monitor detailed Databricks usage patterns.
Unity Catalog lets you easily access and query your account’s operational data, including audit logs, billable usage, and lineage using system tables (Public Preview).
Every good data governance story starts with a strong identity foundation. To learn how to best configure identity in Azure Databricks, see Identity best practices.
Azure Databricks also provides these legacy governance models:
Table access control is a legacy data governance model that lets you programmatically grant and revoke access to objects managed by your workspace’s built-in Hive metastore. Databricks recommends that you use Unity Catalog instead of table access control. Unity Catalog simplifies security and governance of your data by providing a central place to administer and audit data access across multiple workspaces in your account.
Azure Data Lake Storage credential passthrough (legacy) is also a legacy data governance feature that allows you authenticate automatically to Azure Storage from Azure Databricks clusters using the same Microsoft Entra ID identity that you use to log into Azure Databricks. Databricks recommends that you use Unity Catalog instead.
Events
Mar 31, 11 PM - Apr 2, 11 PM
The ultimate Microsoft Fabric, Power BI, SQL, and AI community-led event. March 31 to April 2, 2025.
Register todayTraining
Module
Manage data privacy and governance with Azure Databricks - Training
Manage data privacy and governance with Azure Databricks
Certification
Microsoft Certified: Identity and Access Administrator Associate - Certifications
Demonstrate the features of Microsoft Entra ID to modernize identity solutions, implement hybrid solutions, and implement identity governance.
Documentation
Unity Catalog best practices - Azure Databricks
Learn best practices for setting up data governance and data isolation in Azure Databricks using Unity Catalog and Delta Sharing.
What is Unity Catalog? - Azure Databricks
Learn how to perform data governance in Azure Databricks using Unity Catalog.
Set up and manage Unity Catalog - Azure Databricks
Learn how to set up and administer Unity Catalog for your Azure Databricks account and workspaces.