Databricks-GenAI-Assoc Design Applications Practice Question
An engineer needs to ensure that only authorized users can access the RAG chatbot. Which Databricks security feature should be used to enforce this access control?
⚠ Common exam trap
Candidates often choose workspace-level permissions or generic IAM roles. However, Unity Catalog provides the specific, granular object-level access controls required to secure data assets directly within the RAG pipeline architecture.
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 controls.
Unity Catalog's access control lists (ACLs) provide a robust framework for managing permissions at various levels, including catalog, schema, table, and function. By integrating identity management with these controls, engineers can define granular access to the data and the endpoints behind the chatbot. This ensures that sensitive information is only accessible by verified users, maintaining compliance and enterprise-level data security throughout the system.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Notebook tags.
Why it's wrong here
Notebook tags are for organizational and metadata purposes, not for enforcing security or access control. They do not have the capability to regulate which users can interact with a specific chatbot or access the underlying data sources, making them ineffective for security-critical access management.
- ✗
Cluster environment variables.
Why it's wrong here
Environment variables are used to configure runtime parameters for a cluster, not to enforce security or user-level access controls. They cannot distinguish between authorized and unauthorized users, meaning they have no role in securing the chatbot or controlling who can trigger its functions.
- ✓
Unity Catalog access controls.
Why this is correct
Unity Catalog provides centralized access control that is essential for securing all data assets within Databricks. By defining clear permissions, engineers can ensure that only authenticated and authorized users have access to the data powering the chatbot, which is a fundamental requirement for any secure, enterprise-ready application.
- ✗
The public internet firewall.
Why it's wrong here
While a firewall is part of network security, it does not manage user-level access or data-specific permissions within Databricks. It is a coarse-grained tool that cannot differentiate between authorized users and unauthorized parties once the network connection is established, thus it cannot serve as the primary access control mechanism.
Visual reference
About these practice questions
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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-GenAI-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-GenAI-Assoc exam.