Databricks-DA-Assoc Data Modeling with Databricks SQL Practice Question
A data analyst is working with a Delta table that contains a column 'sensitive_info' which should be redacted for users in the 'marketing' group. The analyst wants to ensure that users in that group see a masked value while other users see the actual data. Which Databricks feature should the analyst use?
⚠ Common exam trap
Test-takers frequently confuse row-level security with column-level masking, or assuming that table ACLs can provide granular column masking.
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
✓
Column masks
Column masks in Unity Catalog are designed to dynamically redact column values based on the user's identity or group membership. They allow the analyst to define a masking expression that applies only to specified users or groups, leaving the original data intact for others. This provides fine-grained security without duplicating data or creating multiple views.
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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Row filters
Why it's wrong here
Row filters are used to restrict which rows a user can see based on a filter condition, not to mask column values. They operate at the row level, not the column level. While row filters could hide entire rows containing sensitive data, the requirement is to redact the column value while still showing the row, so row filters are not appropriate here.
- ✓
Column masks
Why this is correct
Column masks in Unity Catalog allow dynamic masking of column values based on the user's group membership. The analyst can define a mask function that returns a redacted value for the 'marketing' group and the original value for others. This feature is designed exactly for this scenario, providing row-level and column-level security without altering the underlying data.
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Dynamic views
Why it's wrong here
Dynamic views can be used to present a modified version of a table, but they require creating a separate view and managing access to it. While a view could apply a CASE statement to mask the column, it is not a built-in masking feature and does not automatically enforce masking based on group membership. Column masks are the native, centralized solution.
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Table ACLs
Why it's wrong here
Table ACLs control access to the entire table, such as SELECT, MODIFY, or ALL PRIVILEGES. They do not provide column-level masking. Granting or revoking table privileges would either allow full access to all columns or deny access entirely, which does not meet the need to selectively mask a column for a specific group.
About these practice questions
This Databricks-DA-Assoc question is part of Courseiva's 291-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-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.