The answer is Azure Stream Analytics. This service is the correct choice because it is purpose-built for real-time stream processing with sub-second latency, making it ideal for an azure stream processing service for low latency iot scenario where 10,000 events per second must be analyzed and output to Azure Data Lake Storage Gen2 for archival. On the Microsoft Azure Data Engineer Associate DP-203 exam, this question tests your ability to distinguish between ingestion, processing, and orchestration services—a common trap is confusing Azure Event Hubs (ingestion only) or Azure Data Factory (batch orchestration) with actual stream processing. Remember that HDInsight with Spark, while capable of streaming, introduces higher latency and is more suited for complex batch analytics. For quick recall, think: "Stream Analytics streams straight to storage"—it natively integrates with Data Lake Gen2 without extra hops, ensuring low latency from device to archive.
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are designing a streaming data solution for IoT devices that generate 10,000 events per second. The data must be processed with sub-second latency and then stored in Azure Data Lake Storage Gen2 for archival. Which Azure service should you use for the stream processing?
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 designed for real-time stream processing with sub-second latency and can output to Azure Data Lake Storage Gen2. Option A (HDInsight including Spark) is batch-oriented and has higher latency. Option C (Data Factory) is for orchestration, not streaming. Option D (Event Hubs) is an ingestion service, not a processing service.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 HDInsight including Spark Structured Streaming
Why it's wrong here
HDInsight Spark Structured Streaming has higher latency and is more suited for micro-batch processing, not sub-second latency.
✓
Azure Stream Analytics
Why this is correct
Azure Stream Analytics provides sub-second latency stream processing and native output to Azure Data Lake Storage Gen2.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is an orchestration and ETL tool, not a real-time stream processing engine.
✗
Azure Event Hubs
Why it's wrong here
Azure Event Hubs is a data ingestion service, not a processing engine.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Stream Analytics — Azure Stream Analytics is designed for real-time stream processing with sub-second latency and can output to Azure Data Lake Storage Gen2. Option A (HDInsight including Spark) is batch-oriented and has higher latency. Option C (Data Factory) is for orchestration, not streaming. Option D (Event Hubs) is an ingestion service, not a processing service.
What should I do if I get this DP-203 question wrong?
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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