DP-203 Develop data processing Practice Question
You are developing an Azure Stream Analytics job that ingests telemetry from Azure Event Hubs and writes results to an Azure Synapse Analytics dedicated SQL pool. The job must compute a 5-minute tumbling window aggregation and write the aggregated rows to the dedicated SQL pool. You need to configure the output so that each window's aggregated rows are written efficiently. What should you do?
⚠ Common exam trap
The trap here is assuming that any output must go through Blob Storage or Event Hubs before reaching a dedicated SQL pool, when a direct output is available and more efficient.
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
✓
Configure the output to use Azure Synapse Analytics and specify the database and table. Set the batch size to a value that matches the expected number of rows per window.
Stream Analytics provides a native Azure Synapse Analytics output that uses bulk insert mechanisms. The batch size setting controls rows per bulk operation, which directly impacts write efficiency. Writing directly to the dedicated SQL pool avoids intermediate storage and extra processing steps, meeting the requirement for efficient writes of windowed aggregates.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure the output to use Event Hubs and then use a Synapse pipeline to read from Event Hubs and write to the dedicated SQL pool.
Why it's wrong here
Event Hubs is an input source, not an output for aggregated results. Using it as an output would require another consumer to read and write to the pool, adding complexity. Stream Analytics can write directly to the dedicated SQL pool, so this approach is incorrect and inefficient for the given scenario.
- ✗
Configure the output to use Blob Storage and then use an Azure Data Factory Copy activity to load the data into the dedicated SQL pool.
Why it's wrong here
While this two-step approach is possible, it introduces additional latency and operational overhead. The requirement is to write directly to the dedicated SQL pool efficiently. Stream Analytics supports a native Azure Synapse Analytics output, so adding Blob Storage and Data Factory is unnecessary and not the most efficient solution.
- ✓
Configure the output to use Azure Synapse Analytics and specify the database and table. Set the batch size to a value that matches the expected number of rows per window.
Why this is correct
The Azure Synapse Analytics output in Stream Analytics uses bulk insert via PolyBase or COPY, and the batch size controls how many rows are sent per bulk operation. Setting it appropriately for the 5-minute window volume ensures efficient writes and avoids excessive small transactions. This is the correct approach for this scenario.
- ✗
Configure the output to use Azure SQL Database and then create a linked server in the dedicated SQL pool to pull the data.
Why it's wrong here
Azure SQL Database is a different service from a dedicated SQL pool, and linked servers are not supported in dedicated SQL pools. This adds unnecessary complexity and latency. Stream Analytics can write directly to a dedicated SQL pool, so this detour is incorrect and would not meet the requirement efficiently.
Go deeper
Related to this question
Learn chapter
Design and Develop Batch Processing
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 Stream Analytics
Azure Stream Analytics is a fully managed, real-time data processing service that analyzes and transforms high volumes of streaming data from various sources to deliver low-latency insights and trigger actions.
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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
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