- A
Azure Stream Analytics
Stream Analytics is designed for real-time data processing from Event Hubs and can join streams with reference data from SQL Database to enrich and detect patterns like speeding.
- B
Azure Synapse Analytics dedicated SQL pool
Why wrong: Synapse dedicated SQL pool is for large-scale analytics (data warehousing), not for real-time stream processing. It cannot ingest directly from Event Hubs in real time.
- C
Azure Data Factory
Why wrong: Data Factory is an ETL and data orchestration service. It does not perform real-time stream processing or event-based alerting.
- D
Azure Databricks
Why wrong: While Databricks can process streaming data, it requires cluster provisioning and is more complex. Stream Analytics is the simpler, serverless, purpose-built solution for this need.
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 logistics company uses IoT sensors on delivery trucks to transmit GPS location, speed, and engine diagnostics every 10 seconds. The data is ingested into Azure Event Hubs. The company needs to analyze the data in real time to identify speeding trucks and send alerts. The analysis requires joining the live sensor data with a reference table of truck details (e.g., driver name, route number) stored in Azure SQL Database. Which Azure service should they use for the real-time processing?
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 a real-time event processing engine designed to handle streaming data from sources like Azure Event Hubs. It can perform temporal joins between the live IoT sensor stream and a static reference table (e.g., truck details from Azure SQL Database) to enrich the data and trigger alerts when speeding is detected, all with sub-second latency.
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
Stream Analytics is designed for real-time data processing from Event Hubs and can join streams with reference data from SQL Database to enrich and detect patterns like speeding.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Synapse Analytics dedicated SQL pool
Why it's wrong here
Synapse dedicated SQL pool is for large-scale analytics (data warehousing), not for real-time stream processing. It cannot ingest directly from Event Hubs in real time.
- ✗
Azure Data Factory
Why it's wrong here
Data Factory is an ETL and data orchestration service. It does not perform real-time stream processing or event-based alerting.
- ✗
Azure Databricks
Why it's wrong here
While Databricks can process streaming data, it requires cluster provisioning and is more complex. Stream Analytics is the simpler, serverless, purpose-built solution for this need.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse batch-oriented services like Azure Synapse Analytics or Azure Data Factory with real-time processing, or they overcomplicate the solution by choosing Azure Databricks when a simpler, purpose-built service like Stream Analytics is sufficient for the join-and-alert pattern.
Detailed technical explanation
How to think about this question
Under the hood, Azure Stream Analytics uses a SQL-like query language that supports temporal windows (e.g., Tumbling, Hopping, Sliding) and the JOIN clause with the FOR SYSTEM_TIME AS OF keyword to perform point-in-time lookups against reference data. This allows the live GPS stream to be enriched with driver and route details without needing to store the reference data in a separate streaming system. In a real-world scenario, if the reference table is updated infrequently (e.g., daily route assignments), Stream Analytics can automatically refresh the reference data from Azure SQL Database at configurable intervals.
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-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 a real-time event processing engine designed to handle streaming data from sources like Azure Event Hubs. It can perform temporal joins between the live IoT sensor stream and a static reference table (e.g., truck details from Azure SQL Database) to enrich the data and trigger alerts when speeding is detected, all with sub-second latency.
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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