- A
Azure Synapse Analytics
Correct. Azure Synapse Analytics integrates stream processing (via pipelines and Spark/Stream Analytics), batch processing, and serverless SQL to query data lake files directly, all in one platform.
- B
Azure Stream Analytics
Why wrong: Incorrect. Azure Stream Analytics is designed for real-time stream processing only. It cannot handle batch processing of daily inventory files or query data lake files directly with SQL.
- C
Azure Data Lake Analytics
Why wrong: Incorrect. Azure Data Lake Analytics is a batch analytics service that uses U-SQL. It does not support real-time stream processing and is being replaced by Azure Synapse Analytics.
- D
Azure HDInsight
Why wrong: Incorrect. Azure HDInsight is a managed Hadoop/Spark cluster that can handle both batch and stream processing, but it is not a single unified platform for SQL querying of data lake files; it requires more manual setup and management compared to Synapse.
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 chain captures real-time sales data from point-of-sale (POS) systems as a stream of events. The data is ingested into Azure Event Hubs. Additionally, the company receives daily inventory files in CSV format uploaded to Azure Data Lake Storage Gen2. The analytics team needs to combine the streaming sales data with the batch inventory data to generate near real-time dashboards and run historical reports. They want a single analytics platform that can handle both streaming and batch workloads, and allow querying data directly in the data lake using SQL. Which Azure service should they choose?
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 Synapse Analytics
Azure Synapse Analytics is the correct choice because it provides a unified analytics platform that natively integrates with Azure Event Hubs for real-time streaming ingestion and Azure Data Lake Storage Gen2 for batch data. Its Synapse SQL engine supports querying data directly in the data lake using T-SQL, enabling near real-time dashboards and historical reports without data movement. This service is designed to handle both streaming and batch workloads in a single workspace, meeting all the stated requirements.
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 Synapse Analytics
Why this is correct
Correct. Azure Synapse Analytics integrates stream processing (via pipelines and Spark/Stream Analytics), batch processing, and serverless SQL to query data lake files directly, all in one platform.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Stream Analytics
Why it's wrong here
Incorrect. Azure Stream Analytics is designed for real-time stream processing only. It cannot handle batch processing of daily inventory files or query data lake files directly with SQL.
- ✗
Azure Data Lake Analytics
Why it's wrong here
Incorrect. Azure Data Lake Analytics is a batch analytics service that uses U-SQL. It does not support real-time stream processing and is being replaced by Azure Synapse Analytics.
- ✗
Azure HDInsight
Why it's wrong here
Incorrect. Azure HDInsight is a managed Hadoop/Spark cluster that can handle both batch and stream processing, but it is not a single unified platform for SQL querying of data lake files; it requires more manual setup and management compared to Synapse.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Azure Stream Analytics because it handles streaming, but they overlook the requirement for a single platform that also supports batch data and direct SQL querying of the data lake, which Stream Analytics cannot do for historical reports.
Detailed technical explanation
How to think about this question
Azure Synapse Analytics uses a distributed query engine called Synapse SQL, which can query data in Parquet, CSV, or other formats directly in Data Lake Storage Gen2 via external tables or OPENROWSET. For streaming, it integrates with Event Hubs through the Synapse Pipeline or Spark Structured Streaming, allowing real-time data to land in the lake and be queried instantly. A subtle behavior is that Synapse SQL serverless can handle both streaming and batch data without provisioning dedicated compute, but for high-throughput streaming, a dedicated SQL pool or Spark pool may be needed to avoid latency.
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.
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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 Synapse Analytics — Azure Synapse Analytics is the correct choice because it provides a unified analytics platform that natively integrates with Azure Event Hubs for real-time streaming ingestion and Azure Data Lake Storage Gen2 for batch data. Its Synapse SQL engine supports querying data directly in the data lake using T-SQL, enabling near real-time dashboards and historical reports without data movement. This service is designed to handle both streaming and batch workloads in a single workspace, meeting all the stated requirements.
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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