DP-203 Develop data processing Practice Question
You are monitoring an Azure Data Factory pipeline that runs every hour. The pipeline uses a Copy activity to copy data from Azure SQL Database to Azure Blob Storage. Recently, the pipeline has been failing with a 'Timeout' error. The source SQL database has a large number of records. What should you do to resolve the timeout?
⚠ Common exam trap
Many exam-takers assume increasing timeouts (options C or D) will fix the issue, but the real problem is the Copy activity's default command timeout limitation, which requires a fundamentally different data movement approach like staging with PolyBase or COPY statement.
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
✓
Enable staging and use PolyBase or COPY statement for the copy activity.
Enabling staging with PolyBase or the COPY statement offloads the data transfer to Azure Data Lake or Blob Storage, bypassing the bottleneck of the Copy activity's default data movement. This approach is specifically designed for large-scale data loads from Azure SQL Database, as it uses the database's bulk export capabilities and avoids the timeout by not relying on the Copy activity's internal query execution.
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 staging and use PolyBase or COPY statement for the copy activity.
Why this is correct
Staging with PolyBase/COPY allows data to be copied in parallel and avoids timeouts.
- ✗
Decrease the 'writeBatchSize' to 1000.
Why it's wrong here
Decreasing batch size reduces throughput and may increase duration.
- ✗
Increase the 'timeout' value in the copy activity settings.
Why it's wrong here
Increasing timeout may delay failure but does not address the root cause of long-running queries.
- ✗
Use a query with 'queryTimeout' set to 7200 seconds.
Why it's wrong here
Query timeout is for source query execution, not for copy activity timeout.
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
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.
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.
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Same concept, more angles
1 more way this is tested on DP-203
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Refer to the exhibit. You have an Azure Data Factory pipeline that copies data from Azure Blob Storage to Azure SQL Database. The copy activity uses a preCopyScript to truncate the destination table before writing. During a recent run, the copy activity failed after the truncation, leaving the destination table empty. You need to prevent data loss in future failures. What should you modify?
medium- A.Add a retry policy to the copy activity.
- B.Enable fault tolerance in the copy activity source.
- ✓ C.Use a staging table and then a stored procedure to swap tables.
- D.Remove the preCopyScript and set writeBatchSize to 0.
Why C: Using a staging table with a stored procedure swap ensures atomicity: if the copy fails, the staging table is discarded and the original table remains intact. Option A is wrong because a retry policy would re-run the entire activity, including the preCopyScript truncation, and would fail again, causing data loss. Option B is wrong because fault tolerance only skips incompatible rows but does not prevent the truncation from occurring; data loss still happens. Option D is wrong because removing the preCopyScript avoids the truncation but setting writeBatchSize to 0 is invalid; even if fixed, without atomicity, a partial write could lead to data loss on failure.
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.