DP-203 Develop data processing Practice Question
You are building an Azure Stream Analytics job that reads from an Azure Event Hub capturing device telemetry. The job must emit results into an Azure Synapse Analytics dedicated SQL pool. You need to minimize latency and avoid intermediate storage. What should you do?
⚠ Common exam trap
The trap here is assuming that a dedicated SQL pool cannot be written to directly from a streaming job and that data must always be staged in Blob Storage or Data Lake first.
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 Stream Analytics job to output directly to the dedicated SQL pool using the Azure Synapse Analytics output adapter.
Stream Analytics provides a first-class output adapter for Azure Synapse Analytics dedicated SQL pools, enabling direct writes without staging. This minimizes latency and avoids intermediate storage, matching the requirement. The other approaches insert extra services or storage layers, adding delay and operational overhead that the scenario specifically seeks to avoid.
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 job to output to Azure Cosmos DB, then use a Synapse pipeline to copy data into the dedicated SQL pool.
Why it's wrong here
Routing through Cosmos DB adds an unnecessary database and an additional copy activity, which increases latency, cost, and complexity. Cosmos DB is optimized for document workloads, not as a staging area for analytical loads. The dedicated SQL pool can be written to directly by Stream Analytics, so this multi-hop design is needlessly indirect.
- ✓
Configure the Stream Analytics job to output directly to the dedicated SQL pool using the Azure Synapse Analytics output adapter.
Why this is correct
Stream Analytics natively supports Azure Synapse Analytics as an output, writing directly to a dedicated SQL pool table via the built-in connector. This avoids staging the data in Blob Storage or Data Lake, reducing end-to-end latency and eliminating an extra hop. The connector batches rows for efficient inserts, so it suits near-real-time ingestion into a dedicated SQL pool without custom code.
- ✗
Use Azure Functions as the output to insert rows into the dedicated SQL pool.
Why it's wrong here
Azure Functions can write to a dedicated SQL pool, but it adds a compute layer that must scale and manage connections, and it typically results in row-by-row inserts that are inefficient for high-volume telemetry. This increases latency and cost compared to a native output adapter. It also introduces potential throttling and cold-start delays in a streaming context.
- ✗
Write the Stream Analytics output to Azure Blob Storage, then use PolyBase in the dedicated SQL pool to load the data.
Why it's wrong here
This approach introduces an intermediate storage layer and requires a separate PolyBase load step, increasing latency and operational complexity. While PolyBase is efficient for bulk loads, it is not designed for continuous near-real-time ingestion from a streaming job. The scenario explicitly asks to avoid intermediate storage, so this staging pattern is not appropriate.
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 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
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.