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 retail company collects streaming clickstream data from its website into Azure Event Hubs. They need to aggregate the data in real-time to count page views per product every minute and store the results in Azure SQL Database for a live dashboard. Which Azure service should they use to perform this real-time aggregation?
Correct. Stream Analytics is the simplest and most cost-effective service for real-time stream processing with built-in windowing and output to SQL Database.
B
Azure Data Factory
Why wrong: Incorrect. Data Factory is designed for batch data integration and orchestration, not for real-time stream processing.
C
Azure Synapse Pipelines
Why wrong: Incorrect. Synapse Pipelines (built on Data Factory) also focus on batch workflows, not real-time streaming.
D
Azure Databricks
Why wrong: Incorrect. Databricks supports structured streaming, but it requires cluster management and Spark programming, which adds overhead for a task that Stream Analytics can handle more simply.
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 purpose-built for real-time stream processing, allowing you to define a query that aggregates clickstream data from Event Hubs using a tumbling window of one minute to count page views per product. The result can be written directly to Azure SQL Database, enabling a live dashboard without additional orchestration.
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 Stream Analytics
Why this is correct
Correct. Stream Analytics is the simplest and most cost-effective service for real-time stream processing with built-in windowing and output to SQL Database.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Data Factory
Why it's wrong here
Incorrect. Data Factory is designed for batch data integration and orchestration, not for real-time stream processing.
✗
Azure Synapse Pipelines
Why it's wrong here
Incorrect. Synapse Pipelines (built on Data Factory) also focus on batch workflows, not real-time streaming.
✗
Azure Databricks
Why it's wrong here
Incorrect. Databricks supports structured streaming, but it requires cluster management and Spark programming, which adds overhead for a task that Stream Analytics can handle more simply.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Azure Stream Analytics with Azure Data Factory or Synapse Pipelines because both can move data, but only Stream Analytics provides native, low-latency stream processing with temporal windowing for real-time aggregation.
Detailed technical explanation
How to think about this question
Under the hood, Azure Stream Analytics uses a temporal query language based on T-SQL with windowing functions like TumblingWindow, HoppingWindow, and SlidingWindow to partition the stream into finite time slices. The service automatically manages checkpointing and exactly-once semantics, ensuring no data loss or duplication even during failures, which is critical for accurate dashboard metrics.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
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 Stream Analytics — Azure Stream Analytics is purpose-built for real-time stream processing, allowing you to define a query that aggregates clickstream data from Event Hubs using a tumbling window of one minute to count page views per product. The result can be written directly to Azure SQL Database, enabling a live dashboard without additional orchestration.
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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Question Discussion
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