Databricks Data Engineer Associate Question 469
Select 4A data engineering team is tasked with ensuring sensitive customer data is properly secured and access is managed in Databricks. They decide to implement Unity Catalog to enforce fine-grained access controls. Which of the following actions can they take using Unity Catalog to achieve their goals?
- A
Define table-level permissions to restrict access to specific datasets.
- B
Apply data masking to sensitive columns using column-level permissions.
- C
Set up IP address restrictions to limit who can access the Databricks workspace.
- D
Audit data access logs to track and monitor who accessed sensitive data.
- E
Enable row-level security to restrict access to specific rows based on user attributes.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
Unity Catalog is a powerful tool for data governance in Databricks. It enables fine-grained access controls, such as table, column, and row-level permissions, and provides auditing capabilities to monitor data access. However, features like IP address restrictions are managed outside of Unity Catalog, making them irrelevant to this scenario.
- A. Correct.
Correct: Unity Catalog allows defining table-level permissions to control access to specific datasets. This is a key feature for data governance.
- B. Correct.
Correct: Unity Catalog supports column-level permissions, which can be used to apply data masking or restrict access to sensitive columns.
- C. Incorrect.
Incorrect: IP address restrictions are not managed through Unity Catalog. This is typically configured at the Databricks workspace or cloud provider level.
- D. Correct.
Correct: Unity Catalog provides audit logs for tracking and monitoring data access, which is essential for compliance and governance.
- E. Correct.
Correct: Unity Catalog supports row-level security, enabling restrictions on specific rows based on user attributes or roles.