Databricks Data Engineer Professional · 7% practice allocation

Databricks Data Engineer Professional: Data Governance Practice Questions

5 free sample questions from the Data Governance domain, with answers and explanations. The full Data Engineer Professional bank has 311 questions across 10 domains. Questions are scenario-based and written from the official Databricks exam guide.

1.

Why is a centralized governance layer like Unity Catalog preferred over per-workspace, table-by-table access control?

  • A. It provides consistent, centralized governance (permissions, lineage, audit, discovery) across workspaces and clouds from one place✓ Correct
  • B. It makes every table public by default
  • C. It removes the need for any permissions
  • D. It only works for a single table
Explanation

Unity Catalog centralizes governance — access control, lineage, audit, and discovery — consistently across workspaces, avoiding fragmented per-workspace management. It doesn't make data public (B), remove permissions (C), or work for only one table (D).

2.

A security team must review who accessed a sensitive table and when, across the workspace. Which Databricks/Unity Catalog capability supports this?

  • A. Audit logs / access history capturing data access events✓ Correct
  • B. OPTIMIZE ZORDER
  • C. Auto Loader checkpoints
  • D. A broadcast hint
Explanation

Audit logs and Unity Catalog access history record who accessed which data and when, supporting security reviews and compliance. ZORDER (B), Auto Loader checkpoints (C), and broadcast hints (D) don't provide access auditing.

3.

A data steward needs to see how a gold table was derived from upstream sources to assess the impact of a schema change. Which Unity Catalog capability provides this?

  • A. Data lineage (automatically captured table/column lineage)✓ Correct
  • B. A ZORDER index
  • C. A broadcast join
  • D. VACUUM
Explanation

Unity Catalog automatically captures data lineage (table- and column-level), showing upstream/downstream dependencies for impact analysis. ZORDER (B), broadcast joins (C), and VACUUM (D) are performance/maintenance features, not lineage.

4.

To help users discover and classify data (e.g., mark columns as containing PII) in a governed way, which Unity Catalog feature is used?

  • A. Tags (classification metadata) on catalogs, schemas, tables, and columns✓ Correct
  • B. COPY INTO
  • C. dbutils.widgets
  • D. Cluster policies
Explanation

Unity Catalog tags let you classify and label objects/columns (e.g., PII) to aid discovery and governance. Cluster policies (D) govern compute, widgets (C) parameterize notebooks, and COPY INTO (B) ingests data.

5.

What is the correct object hierarchy in Unity Catalog, from broadest to most specific?

  • A. Cluster → Job → Notebook → Cell
  • B. Metastore → Catalog → Schema (database) → Table/View✓ Correct
  • C. Catalog → Metastore → Table → Schema
  • D. Table → Schema → Catalog → Metastore
Explanation

Unity Catalog's three-level namespace is Metastore → Catalog → Schema → Table/View (referenced as catalog.schema.table). Option D reverses it, option A lists compute objects, and option C scrambles the order.

Test yourself across every Data Engineer Professional domain

The free Data Engineer Professional practice test mixes about 20 questions weighted like the exam. The full 311-question bank adds instant grading, flashcards and a timed mock exam.

Take the free Data Engineer Professional practice testPractice the full bank

Study this domain

Data Governance study guide (Data Engineer Professional) →

Other Data Engineer Professional domains

← All Databricks Data Engineer Professional study resources