- A
Use Azure Data Factory with a tumbling window trigger set to 5 minutes.
Why wrong: Data Factory is batch-oriented and the trigger adds overhead; it cannot match the latency of a streaming solution.
- B
Use Azure Stream Analytics with a dedicated SQL pool output and configure a 1-minute window.
Stream Analytics provides sub-minute latency and is designed for real-time ingestion into Synapse dedicated SQL pool.
- C
Use PolyBase to load data from Event Hubs into the dedicated SQL pool every 5 minutes.
Why wrong: PolyBase is for batch loading from external sources, not for streaming ingestion.
- D
Use Spark Structured Streaming in Azure Synapse to write micro-batches every 5 minutes.
Why wrong: Spark Structured Streaming can achieve low latency but often has higher overhead; micro-batches every 5 minutes may not guarantee <5 minutes end-to-end.
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 data processing pipeline in Azure Synapse Analytics that ingests streaming data from Azure Event Hubs and stores it in a dedicated SQL pool. The data must be available for querying within 5 minutes of ingestion. Which processing approach should you recommend?
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
Use Azure Stream Analytics with a dedicated SQL pool output and configure a 1-minute window.
Azure Stream Analytics is purpose-built for real-time stream processing and can output directly to a dedicated SQL pool. By configuring a 1-minute window, you ensure data is materialized in the SQL pool well within the 5-minute SLA, meeting the latency requirement with headroom.
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.
- ✗
Use Azure Data Factory with a tumbling window trigger set to 5 minutes.
Why it's wrong here
Data Factory is batch-oriented and the trigger adds overhead; it cannot match the latency of a streaming solution.
- ✓
Use Azure Stream Analytics with a dedicated SQL pool output and configure a 1-minute window.
Why this is correct
Stream Analytics provides sub-minute latency and is designed for real-time ingestion into Synapse dedicated SQL pool.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use PolyBase to load data from Event Hubs into the dedicated SQL pool every 5 minutes.
Why it's wrong here
PolyBase is for batch loading from external sources, not for streaming ingestion.
- ✗
Use Spark Structured Streaming in Azure Synapse to write micro-batches every 5 minutes.
Why it's wrong here
Spark Structured Streaming can achieve low latency but often has higher overhead; micro-batches every 5 minutes may not guarantee <5 minutes end-to-end.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse batch-oriented tools (Data Factory, PolyBase) or general-purpose streaming frameworks (Spark Structured Streaming) with the dedicated, low-latency stream processing service (Stream Analytics) that is optimized for sub-minute latency to Synapse SQL pools.
Detailed technical explanation
How to think about this question
Azure Stream Analytics uses a temporal windowing mechanism (e.g., tumbling, hopping, or sliding windows) to aggregate or pass-through streaming events before writing to the output sink. When targeting a dedicated SQL pool, Stream Analytics leverages the COPY INTO command or bulk insert for high-throughput writes, and it supports exactly-once semantics via checkpointing and watermarking, ensuring no data loss even under reprocessing scenarios.
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.
TExam Day Tips
- 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 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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this DP-203 question test?
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: Use Azure Stream Analytics with a dedicated SQL pool output and configure a 1-minute window. — Azure Stream Analytics is purpose-built for real-time stream processing and can output directly to a dedicated SQL pool. By configuring a 1-minute window, you ensure data is materialized in the SQL pool well within the 5-minute SLA, meeting the latency requirement with headroom.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 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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