Databricks-DA-Assoc Executing Queries with Databricks SQL Practice Question
A data analyst needs to share a frequently updated sales dashboard with business stakeholders who do not have access to the underlying raw tables containing Personally Identifiable Information (PII). Which Databricks SQL feature should be implemented to securely present this summary data?
⚠ Common exam trap
Candidates frequently confuse dynamic views with static table copies or row-level security implementations, failing to leverage built-in column masking functions for PII protection.
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
✓
Implement dynamic views utilizing column masking and row-level filtering based on user group identities.
Dynamic View Functions with masking policies allow administrators to restrict column-level visibility based on group memberships or user contexts. This ensures stakeholders see aggregated or masked data without requiring separate downstream tables, maintaining strict data governance while enabling seamless visualization sharing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create static CSV extracts of the summary data and upload them to a shared workspace folder.
Why it's wrong here
Static CSV extracts are snapshots, so a frequently updated dashboard would show stale figures, and the files sit outside Unity Catalog governance with no masking or auditing. It is tempting because extracts are quick to produce, but they suit one-off exports, not continuously refreshed dashboards.
- ✗
Grant the stakeholders direct SELECT permissions on the raw tables, relying on them to ignore sensitive columns.
Why it's wrong here
Relying on user discipline to ignore sensitive information violates basic security principles and regulatory compliance standards. Direct table access exposes raw PII, creating severe legal risks and failing the fundamental governance requirement of limiting data exposure.
- ✓
Implement dynamic views utilizing column masking and row-level filtering based on user group identities.
Why this is correct
Dynamic views evaluate user context at query runtime, seamlessly applying masking functions or filtering rows dynamically. This guarantees that unauthorized users viewing the dashboard only see sanitized or aggregated results while retaining a single source of truth.
- ✗
Duplicate the entire dataset into a separate schema, permanently deleting the sensitive columns from the copy.
Why it's wrong here
Duplicating the dataset creates a second copy that must be independently refreshed and governed, so the dashboard drifts from source and PII persists in the copy's lineage. It is tempting as apparent physical separation, but Databricks SQL dynamic views with column masks and row filters present live summary data without replication.
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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.