DP-203 Develop data processing Practice Question
You are designing a near-real-time data processing solution for a retail company. The source is a Kafka cluster on-premises. The target is an Azure Synapse Dedicated SQL Pool. The solution must handle up to 10,000 events per second with less than 5-minute latency. Which Azure service should you use to ingest the data?
⚠ Common exam trap
Test-takers frequently confuse Azure Stream Analytics as an ingestion service, but it is a processing engine that requires an ingestion layer (like Event Hubs) first, and they may overlook that Azure Event Hubs natively supports the Kafka protocol, making it the direct replacement for Kafka ingestion in Azure.
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
✓
Azure Event Hubs (with Kafka protocol support)
Azure Event Hubs with Kafka protocol support is the correct choice because it provides a fully managed, high-throughput data ingestion service that can handle up to 10,000 events per second with sub-second latency, and it natively supports the Kafka protocol, allowing direct integration with your on-premises Kafka cluster without custom code or additional gateways. This meets the near-real-time requirement (<5-minute latency) and scales to the specified throughput.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure Event Hubs (with Kafka protocol support)
Why this is correct
Event Hubs natively ingests Kafka protocol traffic, so the on-premises producers need no reconfiguration, and its partitioned throughput scales past 10,000 events per second, meeting the sub-five-minute latency requirement before loading into the dedicated SQL pool.
- ✗
Azure Data Lake Storage Gen2
Why it's wrong here
Data Lake Storage Gen2 is a storage layer, not a streaming ingestion engine; it cannot pull from Kafka or deliver events into a Dedicated SQL Pool within five minutes. It is tempting because it commonly serves as the landing zone for streamed data, and would be correct as the sink behind a Stream Analytics or Event Hubs pipeline.
- ✗
Azure IoT Hub
Why it's wrong here
IoT Hub is for IoT device telemetry, not Kafka streams.
- ✗
Azure Stream Analytics
Why it's wrong here
Stream Analytics is a stream-processing query engine, not the ingestion mechanism that connects an on-premises Kafka cluster to Azure at 10,000 events per second. It is tempting because it performs the transformation and routing, and would be correct once events already land in Event Hubs or IoT Hub.
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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.