Question 501 of 982
Describe an analytics workload on AzuremediumMultiple ChoiceObjective-mapped

Quick Answer

Azure Synapse Analytics is the correct choice because it delivers a massively parallel processing (MPP) engine that distributes petabyte-scale Parquet data across 60 distributions, allowing complex T-SQL joins and aggregations of billions of rows to complete in seconds. This MPP architecture is what makes it ideal for the scenario, as it splits query work across compute nodes for true parallel execution, and its ability to pause the dedicated SQL pool directly addresses the cost-saving requirement during off-hours. On the DP-900 exam, this question tests your understanding of when to choose Azure Synapse over alternatives like Azure SQL Database or HDInsight; a common trap is selecting Azure SQL Database because it also supports T-SQL, but it lacks the MPP engine needed for petabyte-scale workloads. Remember the memory tip: “Synapse splits, SQL single” — if the scenario mentions massive parallelism, pause capability, and petabyte scale, think 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 financial services company stores petabytes of transaction data in Parquet format in Azure Data Lake Storage Gen2. Data analysts need to run complex SQL queries that join multiple large tables and aggregate billions of rows, with results expected within seconds. The company wants to use a massively parallel processing (MPP) engine that supports T-SQL and can be paused to reduce costs during off-hours. They also need native integration with Azure Data Factory and Power BI. Which Azure service should they use?

Question 1mediummultiple 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 (formerly SQL DW) is the correct choice because it provides a massively parallel processing (MPP) engine that distributes data across 60 distributions, enabling complex T-SQL queries on petabyte-scale Parquet data with results in seconds. It supports native T-SQL, can be paused to reduce costs during off-hours, and offers built-in integration with Azure Data Factory and Power BI through its SQL endpoints and linked service connectors.

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

    Synapse Analytics provides MPP architecture, T-SQL support, pause capability, and tight integration with Azure Data Factory and Power BI, making it ideal for large-scale data warehousing.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Azure HDInsight

    Why it's wrong here

    HDInsight is a managed Hadoop/Spark cluster that uses Hive or Spark SQL, not native T-SQL. It does not have the same pause capability and is more complex to manage for SQL-oriented analysts.

  • Azure Databricks

    Why it's wrong here

    Databricks is a Spark-based analytics platform. While it can handle large datasets, it does not provide a native T-SQL interface or the ability to pause compute resources like Synapse Analytics.

  • Azure SQL Database

    Why it's wrong here

    Azure SQL Database is an OLTP database, not built for petabyte-scale MPP queries. It cannot pause compute and would not provide the performance needed for massive aggregations.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Azure Synapse Analytics with Azure SQL Database or Azure Databricks, not realizing that only Synapse combines MPP architecture, native T-SQL support, pause capability, and direct integration with Azure Data Factory and Power BI for petabyte-scale analytics.

Detailed technical explanation

How to think about this question

Azure Synapse Analytics uses a control node to distribute T-SQL queries across compute nodes, each hosting up to 60 distributions that hash-partition data for parallel processing. The Parquet format in Data Lake Storage Gen2 is read via PolyBase external tables, which push predicate and projection filters down to the storage layer for efficient scanning. Pausing the dedicated SQL pool deallocates compute nodes but retains data in Azure Storage, so you only pay for storage during idle periods.

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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

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 (formerly SQL DW) is the correct choice because it provides a massively parallel processing (MPP) engine that distributes data across 60 distributions, enabling complex T-SQL queries on petabyte-scale Parquet data with results in seconds. It supports native T-SQL, can be paused to reduce costs during off-hours, and offers built-in integration with Azure Data Factory and Power BI through its SQL endpoints and linked service connectors.

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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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.