- A
Azure Data Factory
Why wrong: Data Factory is a batch-oriented orchestration service. It does not natively ingest streaming data without a separate streaming source or custom activity.
- B
Azure Event Hubs with Capture
Event Hubs Capture automatically writes the incoming stream of events to Azure Data Lake Storage in near real-time without any custom code, meeting the requirement exactly.
- C
Azure Stream Analytics
Why wrong: Stream Analytics is used for real-time processing and analytics (e.g., aggregations, pattern matching). It is not designed solely for capturing raw streaming data into files; it would require additional configuration and still involve processing logic.
- D
Azure Synapse Pipelines
Why wrong: Synapse Pipelines are built on Azure Data Factory and are batch-oriented. They cannot natively capture streaming data without custom coding or a streaming source.
DP-900 Describe an analytics workload on Azure Practice Question
This DP-900 practice question tests your understanding of describe an analytics workload on azure. 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 data engineering team needs to build a pipeline that ingests streaming data from IoT devices into Azure Data Lake Storage Gen2. The data arrives as JSON messages. They want to use a service that can capture the streaming data in near real-time and store it as files in the data lake without writing custom code for the ingestion. Which Azure service should they use?
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 Capture
Azure Event Hubs with Capture is the correct choice because it natively ingests streaming JSON data from IoT devices in near real-time and automatically writes the data to Azure Data Lake Storage Gen2 as files without requiring any custom code. The Capture feature automatically persists the event stream to the specified storage destination at defined time or size intervals, making it ideal for serverless, code-free ingestion.
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 Data Factory
Why it's wrong here
Data Factory is a batch-oriented orchestration service. It does not natively ingest streaming data without a separate streaming source or custom activity.
- ✓
Azure Event Hubs with Capture
Why this is correct
Event Hubs Capture automatically writes the incoming stream of events to Azure Data Lake Storage in near real-time without any custom code, meeting the requirement exactly.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Stream Analytics
Why it's wrong here
Stream Analytics is used for real-time processing and analytics (e.g., aggregations, pattern matching). It is not designed solely for capturing raw streaming data into files; it would require additional configuration and still involve processing logic.
- ✗
Azure Synapse Pipelines
Why it's wrong here
Synapse Pipelines are built on Azure Data Factory and are batch-oriented. They cannot natively capture streaming data without custom coding or a streaming source.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Stream Analytics as the primary ingestion service for raw data capture, when in fact Stream Analytics is a processing engine that requires a query and output sink, whereas Event Hubs Capture provides direct, code-free persistence of raw streams.
Detailed technical explanation
How to think about this question
Event Hubs Capture uses a managed checkpoint mechanism that writes Avro or Parquet files to the configured storage account, with configurable time windows (1–15 minutes) or size thresholds (1 MB–500 MB). This ensures exactly-once delivery semantics for the captured data, which is critical for downstream batch processing or analytics. In real-world IoT scenarios, this eliminates the need for a separate stream processor to persist raw data, reducing latency and operational complexity.
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 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.
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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Describe an analytics workload on Azure — study guide chapter
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Event Hubs with Capture — Azure Event Hubs with Capture is the correct choice because it natively ingests streaming JSON data from IoT devices in near real-time and automatically writes the data to Azure Data Lake Storage Gen2 as files without requiring any custom code. The Capture feature automatically persists the event stream to the specified storage destination at defined time or size intervals, making it ideal for serverless, code-free ingestion.
What should I do if I get this DP-900 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 11, 2026
This DP-900 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-900 exam.
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