Question 68 of 982
Describe an analytics workload on AzurehardMultiple ChoiceObjective-mapped

Quick Answer

The answer is Azure Synapse Analytics because it is the only Azure service that provides a unified experience for both stream processing and batch processing within a single platform, eliminating the need to move data between separate systems. This unified real-time and batch analytics capability allows you to ingest streaming clickstream data via Synapse Pipelines or Spark Structured Streaming for real-time dashboards, while simultaneously running complex historical queries on daily sales data and aggregated clickstream data using dedicated or serverless SQL pools. On the DP-900 exam, this question tests your understanding of Azure Synapse Analytics as a converged analytics service, often contrasting it with separate tools like Azure Stream Analytics (stream-only) or Azure Data Lake (batch-only). A common trap is choosing Azure Stream Analytics, which handles real-time processing but lacks native batch querying for historical joins. Memory tip: think of Synapse as the "Swiss Army knife" of analytics—it unifies streams and batches, so you never have to choose between speed and depth.

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 large e-commerce company needs to build an analytics solution. They have streaming clickstream data from their website (JSON) and daily sales data from their transactional database (CSV). They need to perform real-time dashboards on clickstream for the current hour, and also run complex historical queries that join sales data with aggregated clickstream data over the past year. They want a single Azure service that can handle both stream processing and batch processing using a unified experience, without moving data between separate systems. Which Azure service should they use?

Question 1hardmultiple choice
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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 experience for both stream processing (via Synapse Pipelines or Spark Structured Streaming) and batch processing (via dedicated SQL pools or serverless SQL), enabling real-time dashboards on clickstream data and complex historical queries joining sales data with aggregated clickstream data without moving data between separate systems.

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

    Stream Analytics is excellent for real-time stream processing, but it cannot handle complex historical batch queries or join streaming data with large historical datasets without additional services.

  • Azure Data Factory

    Why it's wrong here

    Data Factory is an orchestration and ETL service, not a compute engine for real-time dashboards or complex analytical queries. It can move data but not process it directly.

  • Azure Synapse Analytics

    Why this is correct

    Synapse Analytics provides a unified analytics experience with support for both real-time stream processing (via Synapse Pipelines and Spark structured streaming) and large-scale batch analytics using dedicated SQL pools or serverless SQL. It meets all requirements.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Azure HDInsight

    Why it's wrong here

    HDInsight can run Spark and Hadoop jobs for batch and streaming but requires more manual setup and management, and lacks the built-in unified experience and serverless options of Azure Synapse.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Azure Stream Analytics (a pure stream processor) with a unified analytics service, overlooking that Synapse Analytics can handle both real-time and batch workloads in a single platform without requiring separate data movement or additional services.

Detailed technical explanation

How to think about this question

Azure Synapse Analytics unifies big data and data warehousing by integrating serverless SQL pools for on-demand querying of data lakes, dedicated SQL pools for high-performance analytics, and Apache Spark for stream and batch processing—all within a single workspace. This allows the clickstream JSON data to be ingested via Event Hubs into a dedicated SQL pool for real-time dashboards, while the CSV sales data can be loaded into the same pool for complex historical joins, eliminating the need for separate systems or data movement.

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 Synapse Analytics — Azure Synapse Analytics is the correct choice because it provides a unified experience for both stream processing (via Synapse Pipelines or Spark Structured Streaming) and batch processing (via dedicated SQL pools or serverless SQL), enabling real-time dashboards on clickstream data and complex historical queries joining sales data with aggregated clickstream data without moving data between separate systems.

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

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