- A
Azure Data Factory
Why wrong: Azure Data Factory is a cloud-based ETL and data integration service that orchestrates batch data movement and transformation, not real-time stream processing.
- B
Azure Stream Analytics
Azure Stream Analytics is a real-time analytics service that can process streaming data from sources like Event Hubs, join with reference data, and output results with sub-minute latency.
- C
Azure Databricks
Why wrong: Azure Databricks supports both streaming and batch workloads using Apache Spark, but for a straightforward streaming join, it introduces more complexity and cost than necessary.
- D
Azure Synapse Pipelines
Why wrong: Azure Synapse Pipelines are used for data movement and orchestration in batch scenarios, not for real-time stream processing.
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 receives a continuous stream of customer orders from their website via Azure Event Hubs. They also receive daily inventory updates from suppliers as CSV files uploaded to Azure Blob Storage. The company needs to calculate real-time order fulfillment availability by joining the streaming orders with the latest inventory snapshot. Additionally, they generate nightly sales reports from historical order data. Which Azure service should they use for the real-time processing component?
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 Stream Analytics
Azure Stream Analytics is the correct choice because it is designed for real-time data processing, allowing you to join streaming data from Event Hubs with static or reference data (like the latest inventory snapshot from Blob Storage) using SQL-like queries. This enables the calculation of real-time order fulfillment availability as orders arrive, which is the core requirement.
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
Azure Data Factory is a cloud-based ETL and data integration service that orchestrates batch data movement and transformation, not real-time stream processing.
- ✓
Azure Stream Analytics
Why this is correct
Azure Stream Analytics is a real-time analytics service that can process streaming data from sources like Event Hubs, join with reference data, and output results with sub-minute latency.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Databricks
Why it's wrong here
Azure Databricks supports both streaming and batch workloads using Apache Spark, but for a straightforward streaming join, it introduces more complexity and cost than necessary.
- ✗
Azure Synapse Pipelines
Why it's wrong here
Azure Synapse Pipelines are used for data movement and orchestration in batch scenarios, not for real-time stream processing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Azure Databricks because they associate it with 'real-time' processing, but Stream Analytics is the simpler, more cost-effective, and purpose-built service for this exact pattern of joining streaming data with static reference data.
Trap categories for this question
Scenario analysis trap
Azure Synapse Pipelines are used for data movement and orchestration in batch scenarios, not for real-time stream processing.
Detailed technical explanation
How to think about this question
Under the hood, Azure Stream Analytics uses a temporal join mechanism that automatically handles the concept of 'latest' reference data by loading snapshots from Blob Storage and refreshing them at configurable intervals. This allows the streaming order data to be enriched with the most current inventory levels without needing custom windowing logic, and the output can be sent to Power BI for real-time dashboards or to Azure SQL Database for further processing.
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 Stream Analytics — Azure Stream Analytics is the correct choice because it is designed for real-time data processing, allowing you to join streaming data from Event Hubs with static or reference data (like the latest inventory snapshot from Blob Storage) using SQL-like queries. This enables the calculation of real-time order fulfillment availability as orders arrive, which is the core requirement.
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.
About these practice questions
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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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