Question 821 of 982
Describe an analytics workload on AzurehardMultiple ChoiceObjective-mapped

Quick Answer

The correct choice is Azure Synapse Pipelines plus Azure Stream Analytics because this combination efficiently handles both the daily batch CSV files from Azure Blob Storage and the live web clickstream data from Azure Event Hubs, enabling a near real-time dashboard that refreshes every five minutes. Azure Synapse Pipelines orchestrates the batch ingestion and transformation of the store files, while Azure Stream Analytics processes the streaming clickstream data with low latency, and both outputs can be joined in a destination like Azure Synapse Dedicated SQL Pool for combined querying. On the DP-900 exam, this scenario tests your understanding of hybrid batch-and-streaming architectures, often appearing as a scenario where you must choose services that cover both ingestion patterns without overcomplicating the pipeline. A common trap is selecting only a streaming tool like Stream Analytics alone, forgetting the batch orchestration need, or picking Azure Data Factory without the real-time processing capability. Memory tip: think "Synapse for the schedule, Stream for the speed."

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 needs to blend two data sources for a near real-time dashboard: daily batch files from store systems (CSV files on Azure Blob Storage updated once per day) and live web clickstream data from Azure Event Hubs. The dashboard must refresh every 5 minutes with combined data. Which combination of Azure services should be used to ingest and process both data types most efficiently?

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

C) Azure Synapse Pipelines + Azure Stream Analytics

Option C is correct because Azure Synapse Pipelines can orchestrate the daily batch CSV files from Azure Blob Storage, while Azure Stream Analytics processes the live web clickstream data from Azure Event Hubs in near real-time. Together, they enable a combined data pipeline that refreshes every 5 minutes, meeting the dashboard's latency requirement efficiently.

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.

  • A) Azure Data Factory + Azure Analysis Services

    Why it's wrong here

    Azure Data Factory handles batch but not real-time streaming. Azure Analysis Services is a modeling service, not an ingestion or processing engine.

  • B) Azure Stream Analytics + Power BI

    Why it's wrong here

    Stream Analytics handles real-time data but not batch file processing for CSV dumps. Power BI is a visualization tool, not a data integration service.

  • C) Azure Synapse Pipelines + Azure Stream Analytics

    Why this is correct

    Synapse Pipelines can orchestrate batch ingestion from Blob Storage, and Stream Analytics can process streaming data from Event Hubs, both feeding into Synapse SQL for combined queries.

    Related concept

    Read the scenario before looking for a memorised answer.

  • D) Azure Databricks + Azure Data Lake Storage

    Why it's wrong here

    Databricks can process both batch and streaming, but it requires more management and does not natively provide the dashboard refresh capability; this combination is less targeted for the described scenario.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often assume Power BI alone can handle both batch and streaming ingestion, but it lacks native batch file ingestion from Blob Storage and requires a separate processing service like Stream Analytics for real-time data.

Trap categories for this question

  • Scenario analysis trap

    Databricks can process both batch and streaming, but it requires more management and does not natively provide the dashboard refresh capability; this combination is less targeted for the described scenario.

Detailed technical explanation

How to think about this question

Azure Synapse Pipelines (formerly Azure Data Factory) can schedule and execute Copy activities to load daily CSV files into a staging table, while Azure Stream Analytics uses a temporal join to combine the batch data with the live clickstream stream using a 5-minute tumbling window. This pattern leverages the fact that Stream Analytics can reference static or slowly changing data from Blob Storage via reference data inputs, enabling efficient blending without custom code.

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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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: C) Azure Synapse Pipelines + Azure Stream Analytics — Option C is correct because Azure Synapse Pipelines can orchestrate the daily batch CSV files from Azure Blob Storage, while Azure Stream Analytics processes the live web clickstream data from Azure Event Hubs in near real-time. Together, they enable a combined data pipeline that refreshes every 5 minutes, meeting the dashboard's latency requirement efficiently.

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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