Databricks Governance


            Databricks Governance

Here’s a breakdown of key concepts and features related to Databricks governance, along with some best practices to get you started:

What is Databricks Governance?

Databricks governance encompasses the set of policies, processes, roles, and technologies necessary to ensure data is:

  • Secure:  Safeguarded from unauthorized access or modification.
  • Reliable:  Accurate, consistent, and well-structured.
  • Discoverable: It is easy for approved users to find and understand relevant data.
  • Compliant: Managed by regulatory requirements (e.g., GDPR, CCPA, HIPAA).

Key Tools & Features:

  • Unity Catalog:  Databricks’ primary tool for centralized governance. It allows you to:
    • Manage Fine-Grained Access: Define permissions at the catalog, database, table, and column level.
    • Track Data Lineage: Understand where data comes from and how it’s transformed.
    • Audit Usage: Get detailed logging of all data-related activity for security and compliance purposes.
  • Legacy Governance Tools (Table Access Control): While Unity Catalog is recommended, Databricks still supports more traditional table access controls for managing the built-in Hive metastore permissions.

Best Practices

  • Centralize Governance:  Use Unity Catalog as the single source of truth for permissions and metadata across your Databricks workspaces.
  • Enforce Least Privilege:  Grant only the minimum necessary access to data, reducing risk.
  • Classify Data:  Categorize data based on sensitivity (e.g., restricted, confidential, public) and apply appropriate controls.
  • Establish Clear Ownership: Designate data owners responsible for accuracy, quality, and access decisions for specific data assets.
  • Track Lineage:  Capture transformations and dependencies to aid in troubleshooting and understanding how data is utilized.
  • Utilize Audit Logs:  Monitor data access, modification, sharing, and credential management. This is crucial for compliance reporting and security investigations.

Example: Implementing Fine-Grained Access with Unity Catalog

  1. Create Catalogs: Organize data based on business units or functional areas.
  2. Create Schemas/Databases: Logically structure data assets within catalogs.
  3. Define Tables and Columns: Add descriptive metadata and specify data types.
  4. Create Security Groups: Align groups with roles within your organization (e.g., Data Scientists, Analysts, Data Engineers).
  5. Grant Permissions: Assign groups specific privileges (SELECT, CREATE, MODIFY, etc.) at the catalog, schema, table, or column level.

Key Considerations and Additional Resources

  • Integration with Cloud IAM: Combine Unity Catalog controls with cloud-provider Identity and Access Management (IAM) for multi-layer protection.
  • Regulatory Requirements: Thoroughly understand regulatory requirements that apply to your industry.
  • Version Control and Change Management: Implement versioning for data and code and a formal change management process.

Helpful Links

The Best Learning Online Platform is  Unogeeks Online Training Institute:

Databricks Training Demo Day 1 Video:

You can find more information about Databricks Training in this Dtabricks Docs Link



Unogeeks is the No.1 IT Training Institute for Databricks Training. Anyone Disagree? Please drop in a comment

You can check out our other latest blogs on Databricks Training here – Databricks Blogs

Please check out our Best In Class Databricks Training Details here – Databricks Training

 Follow & Connect with us:


For Training inquiries:

Call/Whatsapp: +91 73960 33555

Mail us at:

Our Website ➜

Follow us:





Leave a Reply

Your email address will not be published. Required fields are marked *