- A
Azure Stream Analytics
Why wrong: Azure Stream Analytics excels at real-time stream processing but is not designed for interactive ad‑hoc queries on historical data stored over months.
- B
Azure Synapse Analytics
Why wrong: Azure Synapse Analytics provides a unified experience for data warehousing and big data analytics, but it is primarily a batch and interactive query platform rather than a real-time streaming engine.
- C
Azure HDInsight
Why wrong: Azure HDInsight offers managed Apache Spark and Hadoop clusters for batch and stream processing, but it lacks a built-in unified query language optimized for both real-time and historical ad‑hoc queries.
- D
Azure Data Explorer
Azure Data Explorer (ADX) is built for real-time analytics on streaming data and interactive queries on large historical datasets using Kusto Query Language (KQL), making it the right choice for this combined workload.
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 needs to analyze clickstream data from their website in real time to detect fraudulent activity and also run complex historical queries on months of data to identify shopping trends. They want a single service that can handle both streaming and batch analytics using a unified query language, minimizing data movement. 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 Data Explorer
Azure Data Explorer (ADX) is designed for real-time analytics on streaming data and can also handle complex historical queries over large volumes of data using the Kusto Query Language (KQL). It minimizes data movement by ingesting streaming data directly and storing it in a columnar format optimized for both real-time and batch queries, making it the ideal single service for this scenario.
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 it's wrong here
Azure Stream Analytics excels at real-time stream processing but is not designed for interactive ad‑hoc queries on historical data stored over months.
- ✗
Azure Synapse Analytics
Why it's wrong here
Azure Synapse Analytics provides a unified experience for data warehousing and big data analytics, but it is primarily a batch and interactive query platform rather than a real-time streaming engine.
- ✗
Azure HDInsight
Why it's wrong here
Azure HDInsight offers managed Apache Spark and Hadoop clusters for batch and stream processing, but it lacks a built-in unified query language optimized for both real-time and historical ad‑hoc queries.
- ✓
Azure Data Explorer
Why this is correct
Azure Data Explorer (ADX) is built for real-time analytics on streaming data and interactive queries on large historical datasets using Kusto Query Language (KQL), making it the right choice for this combined workload.
Related concept
Read the scenario before looking for a memorised answer.
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 is explicitly marketed for real-time streaming, but they overlook the requirement for complex historical queries and a unified query language, which ADX uniquely satisfies with KQL.
Detailed technical explanation
How to think about this question
Azure Data Explorer uses a columnar storage engine with a distributed query execution model that supports both real-time ingestion (via Event Hubs/IoT Hub) and high-performance historical queries using KQL, which includes native time-series functions and aggregation operators. Under the hood, ADX automatically partitions data by ingestion time and uses a sharding mechanism that allows queries to scan only relevant extents, enabling sub-second response times even on terabytes of data. In a real-world clickstream fraud detection scenario, ADX can ingest millions of events per second and run alerting queries with a latency of under 10 seconds while simultaneously serving dashboards for monthly trend analysis without needing to move data between systems.
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.
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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 Data Explorer — Azure Data Explorer (ADX) is designed for real-time analytics on streaming data and can also handle complex historical queries over large volumes of data using the Kusto Query Language (KQL). It minimizes data movement by ingesting streaming data directly and storing it in a columnar format optimized for both real-time and batch queries, making it the ideal single service for this scenario.
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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