DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You have an Azure Data Factory pipeline that copies data from an FTP server to Azure Blob Storage. The pipeline runs successfully most of the time, but occasionally fails with a 'FTP server connection refused' error during peak hours. You need to minimize these failures with minimal cost. 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
✓
Add a retry policy to the copy activity with a backoff interval.
Adding a retry policy with a backoff interval handles transient connection issues. Option D is wrong because increasing parallel copies does not solve connection refused errors. Option B is wrong because Azure ExpressRoute is costly and unnecessary for FTP. Option C is wrong because migrating to SFTP may not resolve connection refused if the server is overloaded.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Add a retry policy to the copy activity with a backoff interval.
Why this is correct
Retry with backoff handles transient connection failures.
- ✗
Set up Azure ExpressRoute to improve network reliability.
Why it's wrong here
Overkill for FTP traffic.
- ✗
Migrate the FTP server to SFTP.
Why it's wrong here
SFTP adds encryption but does not fix connection refused.
- ✗
Increase the parallel copy count in the copy activity.
Why it's wrong here
Parallel copies increase load, may worsen the issue.
Visual reference
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
Learn chapter
Introduction to Azure Data Engineering
Key term
Data Transformation Pipelines
Data transformation pipelines are automated sequences of steps that take raw data from a source, clean and reshape it into a usable format, and then load it into a destination for analysis or storage.
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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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.