DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are monitoring an Azure Data Factory pipeline that copies data from Azure SQL Database to Azure Synapse Analytics. The pipeline occasionally fails with transient errors such as 'Cannot connect to SQL Database' during peak hours. You need to make the pipeline more resilient without manual intervention. What should you configure?
⚠ Common exam trap
The trap here is thinking that increasing DIUs or scheduling more frequent runs will handle transient errors, when only the activity-level retry policy provides automatic re-execution after a failure.
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
✓
Set the retry policy on the Copy activity with a count and interval.
The Copy activity in Azure Data Factory supports a retry policy that automatically re-executes the activity after a failure, with configurable count and interval. This handles transient network or service errors without manual intervention. Other options either address security, throughput, or scheduling but do not provide automatic retry for transient failures within a run.
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 Azure Defender for Azure SQL Database.
Why it's wrong here
Azure Defender provides threat detection and security alerts for Azure SQL Database, but it does not automatically retry failed pipeline activities. It is a monitoring and security feature, not a resilience mechanism for data movement. Enabling it would not address transient connection errors during peak load.
- ✗
Increase the data integration unit (DIU) setting for the Copy activity.
Why it's wrong here
Increasing DIUs can improve throughput and parallel copy performance, but it does not automatically handle transient failures. Higher DIUs might even increase load on the source during peak hours. The requirement is to make the pipeline resilient to intermittent errors, which requires a retry policy rather than more compute resources.
- ✗
Configure a trigger with a recurrence schedule that runs more frequently.
Why it's wrong here
A more frequent schedule does not prevent transient failures within a run; it only starts new pipeline runs more often. If the copy activity fails, a new run may also fail under the same conditions. This approach does not provide automatic retry of the failed operation and could increase load, worsening the issue.
- ✓
Set the retry policy on the Copy activity with a count and interval.
Why this is correct
Configuring a retry policy on the Copy activity allows Azure Data Factory to automatically reattempt the operation after a transient failure. You can specify the number of retries and the interval between them, which handles temporary connectivity issues during peak hours. This is the built-in mechanism for resilience without manual intervention.
Go deeper
Related to this question
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Implement Azure Synapse Analytics
Key term
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
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 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.