Databricks-DE-Assoc Databricks Intelligence Platform Practice Question
A data engineer is designing a secure architecture using the Databricks Intelligence Platform. Which TWO of the following statements accurately describe the role and capabilities of Unity Catalog within this platform? (Choose TWO)
⚠ Common exam trap
A common misconception is that Unity Catalog operates locally within a single workspace or manages underlying cloud virtual machines. In reality, a Unity Catalog metastore can be shared across multiple workspaces in an account.
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 provides centralized access control for tables, views, volumes, and AI models across multiple workspaces.
Unity Catalog is the fine-grained governance solution for data and AI across the Databricks platform, centralizing access control for tables, volumes, and models. It operates across multiple workspaces in a metastore, ensuring consistent security policies and audit logging regardless of which workspace or compute resource executes the user queries.
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 provides centralized access control for tables, views, volumes, and AI models across multiple workspaces.
Why this is correct
Unity Catalog centralizes governance by defining permissions once in an account-level metastore and applying them consistently across all attached workspaces. This architecture simplifies auditing and ensures uniform security standards for both structured data and machine learning artifacts.
- ✗
Unity Catalog replaces the underlying cloud provider IAM roles for all compute resources executing queries.
Why it's wrong here
Unity Catalog governs data and AI assets through its own privilege model, but compute still assumes cloud provider IAM roles for storage and resource access; it does not replace them. Unity Catalog's role is centralised governance, auditing and fine-grained access control across workspaces, not IAM substitution.
- ✓
Unity Catalog maintains a single, unified metastore that can be shared across multiple workspaces within the same account.
Why this is correct
A single Unity Catalog metastore can be associated with multiple Databricks workspaces across an entire account. This enables seamless data sharing and collaborative analytics without duplicating governance definitions or data assets across different business units.
- ✗
Unity Catalog automatically handles the physical partitioning of Delta tables for optimal query performance.
Why it's wrong here
Physical data layout optimization, such as Z-ordering and file compaction using OPTIMIZE commands, is performed by the compute engine rather than Unity Catalog itself. Unity Catalog focuses on metadata management, data lineage, and access permissions.
- ✗
Unity Catalog requires all data to be migrated into proprietary binary formats before governance policies can be applied.
Why it's wrong here
Unity Catalog governs data stored in standard cloud storage formats, with a heavy emphasis on open table formats like Delta Lake and Parquet. It does not force migration into proprietary binary formats to enforce fine-grained security policies.
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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-DE-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-DE-Assoc exam.