DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are a data engineer at a logistics company. You have an Azure Data Lake Storage Gen2 account that stores JSON logs from IoT devices. The logs are written continuously and are stored in a folder structure of /logs/{year}/{month}/{day}/{hour}/. You need to optimize the storage for cost and performance. The data is accessed frequently for the first 30 days, then occasionally for the next 60 days, and rarely after that. You need to minimize storage costs while ensuring that data remains available. What should you do?
⚠ Common exam trap
It's easy for candidates to confuse data protection features like soft delete or access control mechanisms with cost optimization, when the requirement is specifically about automatically moving data to cheaper tiers based on age.
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
✓
Configure a lifecycle management policy to move blobs to the Cool tier after 30 days and to the Archive tier after 90 days.
Lifecycle management policies in Azure Storage automatically transition blobs between Hot, Cool, and Archive tiers based on rules you define. This matches the access pattern: frequent access for 30 days (Hot), occasional for next 60 days (Cool), and rare thereafter (Archive). It minimizes storage costs without manual intervention, and data remains available (Archive requires rehydration). This is the most efficient and cost-effective solution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable soft delete for blobs and set the retention period to 90 days.
Why it's wrong here
Soft delete protects against accidental deletion but does not change the storage tier or reduce costs. It retains deleted data for a specified period, which incurs additional storage costs. This does not address the requirement to optimize storage costs based on access frequency. Soft delete is a data protection feature, not a cost optimization strategy.
- ✗
Create a scheduled Azure Data Factory pipeline that moves data older than 30 days to a separate storage account with the Cool tier, and older than 90 days to the Archive tier.
Why it's wrong here
This approach requires custom development, maintenance, and incurs data movement costs. It also does not automatically handle tiering within the same account. Lifecycle management policies are native, server-side, and require no code. The custom pipeline adds complexity and potential for errors, and it may not be as cost-effective due to transaction costs.
- ✓
Configure a lifecycle management policy to move blobs to the Cool tier after 30 days and to the Archive tier after 90 days.
Why this is correct
Azure Blob Storage lifecycle management policies can automatically transition blobs between access tiers based on age. Moving data to Cool after 30 days reduces storage costs for infrequently accessed data, and moving to Archive after 90 days further reduces costs for rarely accessed data. This aligns with the access pattern and minimizes costs while keeping data available (though Archive requires rehydration for access).
- ✗
Use Azure Data Lake Storage Gen2 hierarchical namespace and set POSIX permissions to restrict access to older data.
Why it's wrong here
Hierarchical namespace and POSIX permissions control access, not storage costs or performance. They do not change the storage tier or lifecycle. While they are useful for security, they do not meet the cost optimization requirement. The scenario requires tiering based on access patterns, which is handled by lifecycle management.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
About these practice questions
One of 509 original DP-203 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. 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 Microsoft exam blueprint
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.