DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
Your company has a data lake in Azure Data Lake Storage Gen2 that stores sensitive customer information. You need to implement fine-grained access control so that data engineers can read all data, data scientists can read only anonymized data, and auditors can view access logs. The solution must use Azure role-based access control (RBAC) and access control lists (ACLs). You also need to enable auditing of read operations. What should you do?
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
✓
Assign Storage Blob Data Contributor RBAC role to data engineers at the storage account level, use ACLs to deny read access to raw data for data scientists, and enable diagnostic settings for read requests to Log Analytics.
To implement fine-grained access control in Azure Data Lake Storage Gen2, combine Azure RBAC roles for coarse permissions (e.g., Storage Blob Data Contributor for data engineers at the storage account level) and ACLs for fine-grained control (e.g., deny read on raw data for data scientists). Enable diagnostic settings for read requests to Log Analytics to audit read operations. Option A is incorrect because assigning Storage Blob Data Reader to data scientists would give them read access to all data, not just anonymized data, and lifecycle management does not control access. Option C is incorrect because Storage Analytics logs are deprecated; diagnostic settings should be used instead. Option D is incorrect because granting read access to all users at the container level is overly permissive and does not provide fine-grained control; Azure Policy is for compliance, not access control.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure RBAC to assign Storage Blob Data Reader to data scientists, and configure lifecycle management to move raw data to archive tier.
Why it's wrong here
Lifecycle management doesn't anonymize.
- ✓
Assign Storage Blob Data Contributor RBAC role to data engineers at the storage account level, use ACLs to deny read access to raw data for data scientists, and enable diagnostic settings for read requests to Log Analytics.
Why this is correct
Provides fine-grained control and auditing.
- ✗
Assign RBAC roles at the storage account level and enable Storage Analytics logs for read operations.
Why it's wrong here
Storage Analytics logs are deprecated.
- ✗
Assign RBAC roles at the container level to grant read access to all users, and use Azure Policy to audit access.
Why it's wrong here
No fine-grained control.
Visual reference
Quick reference
Access Control Model Comparison
| Model | Acronym | Who Controls Access? | Best For |
|---|---|---|---|
| Discretionary Access Control | DAC | Resource owner | Small teams, file shares |
| Mandatory Access Control | MAC | System / security labels | Classified govt / military |
| Role-Based Access Control | RBAC | Administrator (via roles) | Enterprise environments |
| Attribute-Based Access Control | ABAC | Policy engine (user + resource attributes) | Fine-grained, dynamic policies |
| Rule-Based Access Control | RuBAC | System rules / ACLs | Firewall rules, network ACLs |
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 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-203 exam.