easyMultiple ChoiceObjective-mapped
DP-203 Practice Question: A company ingests streaming data from IoT devices…
A company ingests streaming data from IoT devices into Azure Event Hubs. The data must be processed in near real-time to detect anomalies and stored in Azure Data Lake Storage Gen2 for historical analysis. The solution must minimize latency and avoid duplicate processing. Which Azure service should be used for processing?
⚠ Common exam trap
Candidates often choose Azure Databricks with Structured Streaming because of its flexibility and popularity, but they overlook the specific requirement for minimal latency and built-in exactly-once processing, which Azure Stream Analytics handles more efficiently without the overhead of a Spark cluster.
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 Stream Analytics
Azure Stream Analytics is the correct choice because it is purpose-built for near real-time stream processing with sub-second latency, directly integrates with Event Hubs as input and Data Lake Storage Gen2 as output, and provides built-in exactly-once delivery semantics to avoid duplicate processing. It also supports temporal windowing and anomaly detection functions natively, making it ideal for this IoT anomaly detection scenario.
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 Data Factory
Why it's wrong here
Azure Data Factory is for batch orchestration, not real-time streaming.
- ✗
Azure Databricks with Structured Streaming
Why it's wrong here
Azure Databricks can process streams but has higher latency and complexity compared to Stream Analytics for this scenario.
- ✗
Azure Functions with Event Hubs trigger
Why it's wrong here
Azure Functions can process events but lacks built-in stream processing features like windowing and exactly-once.
- ✓
Azure Stream Analytics
Why this is correct
Azure Stream Analytics provides low-latency stream processing with exactly-once semantics and integrates with Event Hubs and Data Lake Storage.
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Senior Network & Security Engineer · founder of Courseiva
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