Question 207 of 760
DP-203 Develop data processing Practice Question
You are designing a data processing solution for an e-commerce company that uses Azure Synapse Analytics. The solution must process clickstream data from a web application. The data arrives in JSON format through Azure Event Hubs. You need to load the data into a dedicated SQL pool every 5 minutes with minimal latency. The data volume is about 100 MB every 5 minutes. You want to use PolyBase for loading. Which approach should you use?
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 Azure Data Factory with a Copy activity to copy data from Event Hubs to Azure Data Lake Storage Gen2 as JSON files, then use a PolyBase activity to load from ADLS Gen2 to the dedicated SQL pool.
It uses Azure Data Factory to stage the JSON data from Event Hubs into Azure Data Lake Storage Gen2 (ADLS Gen2) as JSON files, and then uses a PolyBase activity to load the data from ADLS Gen2 into the dedicated SQL pool. This approach meets the requirement of using PolyBase for loading, handles the 100 MB every 5 minutes with minimal latency, and leverages the efficient bulk loading capability of PolyBase. Option A is incorrect because Azure Stream Analytics does not support output directly to a dedicated SQL pool; it can output to Azure SQL Database or other sinks, but not dedicated SQL pool, and it does not use PolyBase. Option C is incorrect because using Azure Databricks with JDBC does not utilize PolyBase and would require a continuously running cluster, increasing cost and complexity. Option D is incorrect because PolyBase cannot create an external data source pointing directly to Event Hubs; PolyBase external data sources only support Azure Blob Storage, ADLS Gen2, and Hadoop, not Event Hubs.
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 Azure Stream Analytics to transform the JSON data and output directly to the dedicated SQL pool.
Why it's wrong here
Less efficient for small frequent loads and adds complexity.
- ✓
Use Azure Data Factory with a Copy activity to copy data from Event Hubs to Azure Data Lake Storage Gen2 as JSON files, then use a PolyBase activity to load from ADLS Gen2 to the dedicated SQL pool.
Why this is correct
Simplifies staging and leverages PolyBase for efficient loading.
- ✗
Use Azure Databricks to read from Event Hubs, transform the data, and write to the dedicated SQL pool using JDBC.
Why it's wrong here
Higher cost due to continuous cluster.
- ✗
Use PolyBase directly from Event Hubs to dedicated SQL pool by creating an external data source that points to Event Hubs.
Why it's wrong here
PolyBase does not support Event Hubs as a data source.
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 |
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Last reviewed: Jun 21, 2026
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