Databricks-DE-Assoc Databricks Intelligence Platform Practice Question
Which feature of the Databricks Intelligence Platform allows users to manage fine-grained access control across workspaces for tables, files, and machine learning models?
⚠ Common exam trap
Candidates often confuse workspace-level ACLs with platform-wide data governance tools, choosing legacy permissions instead of modern catalog solutions.
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
Unity Catalog is the centralized governance layer within the Databricks Intelligence Platform. It provides a single interface to manage permissions across the entire data estate. This is vital for security and compliance because it eliminates the need for siloed permission management in individual workspaces, ensuring that security policies are consistently applied and auditable across all users, data assets, and compute resources in the platform.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Cluster Policies
Why it's wrong here
Cluster policies are designed to control the configuration of compute resources, such as limiting the number of workers or instance types. They focus on cost management and resource allocation rather than managing access control for data, tables, or machine learning models across the entire platform.
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Workspace Admin Settings
Why it's wrong here
Workspace admin settings provide local control over individual workspace configurations, including user management and basic service settings. However, they lack the capability to provide centralized, fine-grained access control for data assets and AI models that span multiple workspaces within a single Databricks account.
- ✓
Unity Catalog
Why this is correct
Unity Catalog acts as a centralized governance layer, allowing administrators to define security policies once and apply them globally. It supports fine-grained access control at the catalog, schema, table, and file level, which is essential for ensuring security and compliance across modern enterprise data lakehouse architectures.
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Secret Scopes
Why it's wrong here
Secret scopes are used to securely manage sensitive information like database credentials, API keys, or passwords. While they help keep sensitive data out of plain text code, they are not designed to manage granular permissions for data objects, tables, or machine learning models within the platform.
About these practice questions
This Databricks-DE-Assoc question is part of Courseiva's 276-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.