DP-203 Develop data processing Practice Question
Which TWO options are correct for configuring a copy activity in Azure Data Factory to load data from Azure Blob Storage to Azure SQL Database?
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
✓
Use a staging table in Azure SQL Database before inserting into the final table.
Correct options are A and B. Option A (using a staging table in Azure SQL Database before inserting into the final table) is a best practice for large data loads, enabling efficient truncate-and-reload or upsert operations. Option B (using staging via Azure Blob Storage when loading large volumes) improves performance by batching and parallelizing the load, reducing timeouts and resource contention. Option D is incorrect because PolyBase is not supported for Azure SQL Database; it is available only for Azure Synapse Analytics and SQL Server. Option C is incorrect because Azure Data Lake Storage is not the standard staging location for Azure SQL Database; Azure Blob Storage is used. Option E is incorrect because skipping staging can degrade performance for large data volumes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use a staging table in Azure SQL Database before inserting into the final table.
Why this is correct
Staging table allows data validation and transformation before final load.
- ✓
Use staging via Azure Blob Storage when loading large volumes to improve performance.
Why this is correct
Staging via Blob Storage can improve load performance for large datasets.
- ✗
Use Azure Data Lake Storage as the staging location for better throughput.
Why it's wrong here
Azure SQL Database does not support Data Lake Storage as staging.
- ✗
Use PolyBase to load directly from Blob Storage to Azure SQL Database.
Why it's wrong here
PolyBase is supported for Synapse, not Azure SQL Database.
- ✗
Always skip staging to reduce latency.
Why it's wrong here
Skipping staging may cause timeouts for large datasets.
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
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.
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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.