Databricks-DA-Assoc Understanding the Databricks Platform Practice Question
A data analyst is new to a Databricks workspace and needs to work with data stored in Unity Catalog. The analyst wants to understand which statements about Unity Catalog are accurate. (Choose two.)
⚠ Common exam trap
The trap here is mixing up Unity Catalog with the older workspace-local Hive metastore, leading to false beliefs that grants are per-workspace or that only notebooks can query governed data.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Unity Catalog access control can be applied at the catalog, schema, table, and column levels, including row and column filters.
Unity Catalog centralizes governance with a three-level namespace and supports privileges from the catalog level down to columns, including row filters and column masks. These two characteristics let an analyst reference data with fully qualified names and trust that access rules are enforced consistently. The other statements misstate storage requirements, metadata placement, or the range of supported query interfaces.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Unity Catalog access control can be applied at the catalog, schema, table, and column levels, including row and column filters.
Why this is correct
Unity Catalog supports fine-grained privileges at multiple levels, and it also supports row filters and column masks attached to tables. This lets administrators grant broad access to a catalog or schema while restricting sensitive rows or columns for specific users or groups. The unified privilege model means analysts see only the data they are entitled to, regardless of the query tool they use.
- ✓
Unity Catalog provides a centralized governance model with a three-level namespace of catalog, schema, and table or view.
Why this is correct
Unity Catalog organizes data objects under a metastore using the three-level namespace catalog.schema.object. This structure centralizes metadata and access control across workspaces, so permissions granted on a catalog, schema, or object apply consistently. For an analyst, this means fully qualified names like main.sales.orders identify data unambiguously, and governance is managed in one place rather than per workspace.
- ✗
Unity Catalog metadata is stored separately in each workspace, so grants must be repeated for every workspace.
Why it's wrong here
A core benefit of Unity Catalog is that metadata and grants live in a central metastore attached to multiple workspaces. Users and groups are defined once, and privileges apply across all attached workspaces. Repeating grants per workspace describes legacy workspace-local Hive metastore behavior, not Unity Catalog, so this statement is incorrect for the scenario.
- ✗
Unity Catalog can only be queried from notebooks and not from Databricks SQL warehouses or dashboards.
Why it's wrong here
Unity Catalog is accessible from notebooks, Databricks SQL warehouses, jobs, and dashboards, as well as external clients through supported connectors. The governance layer is independent of the compute or interface used. Claiming it works only in notebooks contradicts how Unity Catalog is designed to unify access, so this option does not accurately describe the platform.
- ✗
Unity Catalog requires that all tables be stored as external tables in cloud object storage rather than managed tables.
Why it's wrong here
Unity Catalog supports both managed and external tables. Managed tables have their data files and lifecycle managed by Unity Catalog in a configured storage location, while external tables reference paths the user controls. Requiring only external tables is not a Unity Catalog rule, so this statement misrepresents how storage and lifecycle are handled for governed tables.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DA-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DA-Assoc exam.