Quick Answer
The answer is Azure Stream Analytics, as it is the only service that natively provides exactly-once semantics for streaming data from Event Hubs to Azure Synapse. This is achieved through checkpointing and transactional output, ensuring that each event is processed and written exactly once even when late-arriving data is handled via configurable watermarks and out-of-order policies. On the DP-203 exam, this scenario tests your understanding of stream processing guarantees versus batch-oriented tools; a common trap is choosing Spark Structured Streaming in Synapse, which requires complex custom logic for exactly-once delivery to Synapse, or Azure Data Factory, which is designed for batch ingestion only. Remember the key distinction: for real-time, exactly-once streaming to Synapse, always pick Azure Stream Analytics. A useful memory tip is “ASA for exactly-once to Synapse—no Spark, no batch, no fuss.”
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.
A company is ingesting streaming data from IoT devices into Azure Event Hubs. The data must be processed in near real-time and stored in Azure Synapse Analytics for reporting. The solution must handle late-arriving data and ensure exactly-once semantics. Which Azure service should you use for stream processing?
Azure Data Factory with Event Hubs source
Why wrong: Data Factory is batch-oriented.
Azure Synapse Spark Structured Streaming
Why wrong: Complex to achieve exactly-once; checkpointing required.
Azure Stream Analytics
Provides exactly-once delivery and can handle late arrivals.
Azure Event Hubs with Capture
Why wrong: Capture is for storage, not processing.
Answer choices
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
Option D is correct because Azure Stream Analytics supports exactly-once semantics to Synapse, handles late arrivals, and is optimized for real-time. Option A is incorrect because Spark Structured Streaming in Synapse does not provide exactly-once to Synapse out of the box. Option B is incorrect because Event Hubs itself does not process data. Option C is incorrect because Data Factory is for batch, not streaming.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure Data Factory with Event Hubs source
Why it's wrong here
Data Factory is batch-oriented.
Azure Synapse Spark Structured Streaming
Why it's wrong here
Complex to achieve exactly-once; checkpointing required.
Azure Stream Analytics
Why this is correct
Provides exactly-once delivery and can handle late arrivals.
Related concept
Read the scenario before looking for a memorised answer.
Azure Event Hubs with Capture
Why it's wrong here
Capture is for storage, not processing.
Common exam traps
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
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.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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.
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FAQ
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Stream Analytics — Option D is correct because Azure Stream Analytics supports exactly-once semantics to Synapse, handles late arrivals, and is optimized for real-time. Option A is incorrect because Spark Structured Streaming in Synapse does not provide exactly-once to Synapse out of the box. Option B is incorrect because Event Hubs itself does not process data. Option C is incorrect because Data Factory is for batch, not streaming.
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.
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 21, 2026
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.
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