DP-203 Develop data processing Practice Question
You have an Azure Data Factory pipeline that copies data from an on-premises SQL Server to Azure Blob Storage. The pipeline uses a self-hosted integration runtime. You notice that the copy activity fails intermittently with the error: 'Failure happened on 'Source' side. ErrorCode=SqlOperationFailed'. The on-premises SQL Server is under heavy load during business hours. What is the most likely cause?
⚠ Common exam trap
Many exam-takers confuse a source-side error with a sink-side error, or assume that any intermittent failure must be a network or connectivity issue, rather than recognizing that SQL Server resource contention under heavy load is a classic cause of intermittent 'SqlOperationFailed' errors.
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
✓
The SQL Server is experiencing resource contention or timeout due to heavy load.
The error 'SqlOperationFailed' on the source side indicates that the SQL Server itself is failing to complete the query or data extraction operation. Under heavy load, the SQL Server may experience resource contention (CPU, memory, I/O) or reach query timeout thresholds, causing the copy activity to fail intermittently. This is consistent with the described scenario of heavy load during business hours.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The SQL Server is experiencing resource contention or timeout due to heavy load.
Why this is correct
Intermittent failures often due to resource pressure.
- ✗
The Azure Blob Storage account is throttling requests.
Why it's wrong here
Error is on source side.
- ✗
The authentication method to SQL Server is incorrect.
Why it's wrong here
Would cause persistent failure.
- ✗
The self-hosted integration runtime is not connected to the network.
Why it's wrong here
Would fail consistently.
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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