- A
A. Azure SQL Database
Why wrong: Azure SQL Database is a relational database service optimized for OLTP workloads. It does not natively query external files in a data lake without additional tools like PolyBase, and it is not designed for petabyte-scale analytics on Parquet files.
- B
B. Azure Synapse Serverless SQL pool
Serverless SQL pool in Azure Synapse Analytics provides a distributed query engine that can query data directly in Azure Data Lake Storage (including Parquet) using T-SQL. It is serverless, scales automatically, and charges per query, making it ideal for interactive ad-hoc analytics.
- C
C. Azure HDInsight
Why wrong: Azure HDInsight is a managed Hadoop/Spark cluster service. While it can query Parquet files, it requires provisioning and managing clusters, which does not meet the 'without managing infrastructure' requirement.
- D
D. Azure Data Factory
Why wrong: Azure Data Factory is an ETL and data orchestration service used to move and transform data. It is not a query engine; it cannot run interactive SQL queries directly on data.
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 data analyst needs to run interactive SQL queries against petabytes of sales data stored in Parquet format in Azure Data Lake Storage Gen2. The analyst wants the fastest query performance for ad-hoc exploration without provisioning or managing any infrastructure. 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
B. Azure Synapse Serverless SQL pool
Azure Synapse Serverless SQL pool is correct because it enables running interactive T-SQL queries directly against Parquet files in Azure Data Lake Storage Gen2 without provisioning any infrastructure. It uses a pay-per-query model and leverages a distributed query engine to deliver fast performance on petabytes of data, making it ideal for ad-hoc exploration.
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 SQL Database
Why it's wrong here
Azure SQL Database is a relational database service optimized for OLTP workloads. It does not natively query external files in a data lake without additional tools like PolyBase, and it is not designed for petabyte-scale analytics on Parquet files.
- ✓
B. Azure Synapse Serverless SQL pool
Why this is correct
Serverless SQL pool in Azure Synapse Analytics provides a distributed query engine that can query data directly in Azure Data Lake Storage (including Parquet) using T-SQL. It is serverless, scales automatically, and charges per query, making it ideal for interactive ad-hoc analytics.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
C. Azure HDInsight
Why it's wrong here
Azure HDInsight is a managed Hadoop/Spark cluster service. While it can query Parquet files, it requires provisioning and managing clusters, which does not meet the 'without managing infrastructure' requirement.
- ✗
D. Azure Data Factory
Why it's wrong here
Azure Data Factory is an ETL and data orchestration service used to move and transform data. It is not a query engine; it cannot run interactive SQL queries directly on data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Synapse Serverless SQL pool with Azure SQL Database, assuming both are for querying data, but Azure SQL Database cannot directly query external files in Data Lake Storage without additional tools like PolyBase.
Detailed technical explanation
How to think about this question
Azure Synapse Serverless SQL pool uses a distributed query processing engine that reads data directly from Data Lake Storage via the Azure Blob Filesystem (ABFS) driver, pushing down filter and aggregation operations to the storage layer for optimal performance. It supports OPENROWSET with BULK operations to query Parquet files, and its automatic statistics generation helps optimize query plans without manual tuning. In real-world scenarios, this service is ideal for data lakehouse architectures where analysts need to explore raw data without moving it into a traditional warehouse.
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.
- →
Describe an analytics workload on Azure — study guide chapter
Learn the concepts, then practise the questions
- →
Describe an analytics workload on Azure practice questions
Targeted practice on this topic area only
- →
All DP-900 questions
982 questions across all exam domains
- →
Microsoft Azure Data Fundamentals DP-900 study guide
Full concept coverage aligned to exam objectives
- →
DP-900 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Describe core data concepts practice questions
Practise DP-900 questions linked to Describe core data concepts.
Describe an analytics workload on Azure practice questions
Practise DP-900 questions linked to Describe an analytics workload on Azure.
Identify considerations for relational data on Azure practice questions
Practise DP-900 questions linked to Identify considerations for relational data on Azure.
Describe considerations for working with non-relational data on Azure practice questions
Practise DP-900 questions linked to Describe considerations for working with non-relational data on Azure.
DP-900 fundamentals practice questions
Practise DP-900 questions linked to DP-900 fundamentals.
DP-900 scenario practice questions
Practise DP-900 questions linked to DP-900 scenario.
DP-900 troubleshooting practice questions
Practise DP-900 questions linked to DP-900 troubleshooting.
Practice this exam
Start a free DP-900 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
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: B. Azure Synapse Serverless SQL pool — Azure Synapse Serverless SQL pool is correct because it enables running interactive T-SQL queries directly against Parquet files in Azure Data Lake Storage Gen2 without provisioning any infrastructure. It uses a pay-per-query model and leverages a distributed query engine to deliver fast performance on petabytes of data, making it ideal for ad-hoc exploration.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.