DP-300 Implement a secure environment Practice Question
Your company uses Azure SQL Database and wants to implement row-level security (RLS) to restrict access to customer data based on the user's Microsoft Entra ID group membership. Which TWO actions are required?
⚠ Common exam trap
A common mix-up: candidates confuse row-level security with dynamic data masking or Always Encrypted, assuming that hiding or encrypting columns is equivalent to restricting row access, but RLS specifically filters rows based on user attributes, not column-level 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
✓
Create a security policy that uses a predicate function.
Row-level security (RLS) in Azure SQL Database restricts data access at the row level by using a security policy that invokes a predicate function. The predicate function defines the logic for filtering rows, such as checking the caller's Microsoft Entra ID group membership via IS_MEMBER(). Therefore, creating both the predicate function (Option E) and the security policy that uses it (Option C) are required steps.
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 a column master key for the secured columns.
Why it's wrong here
Column master keys are for Always Encrypted, not RLS.
- ✗
Grant the user the db_securityadmin server role.
Why it's wrong here
Server roles are not required for RLS.
- ✓
Create a security policy that uses a predicate function.
Why this is correct
A security policy enforces the predicate.
- ✗
Apply a dynamic data masking rule to hide sensitive columns.
Why it's wrong here
DDM masks data, it does not filter rows.
- ✓
Create a predicate function that filters rows based on the user's group membership.
Why this is correct
The predicate function defines the filter logic.
Go deeper
Related to this question
Learn chapter
Overview of Azure Data Platform Options
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-300 practice question is part of Courseiva's free Microsoft 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 DP-300 exam.