- A
Azure Data Factory
Why wrong: Incorrect. Azure Data Factory is used for data integration and orchestration, not for running ad-hoc SQL queries on data.
- B
Azure Synapse Serverless SQL pool
Correct. Serverless SQL pool in Azure Synapse allows you to query data in Data Lake Storage using T-SQL without moving it, enabling ad-hoc analysis with minimal setup.
- C
Azure SQL Database
Why wrong: Incorrect. Azure SQL Database requires data to be loaded into the database first, which involves data movement and additional costs, contrary to the requirement of keeping data in place.
- D
Azure HDInsight
Why wrong: Incorrect. HDInsight is a managed Hadoop/Spark service that can query data in Data Lake, but it requires using Hive or Spark SQL, not standard T-SQL, and is more complex than needed for simple SQL queries.
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 company stores terabytes of web server log data in CSV files in Azure Data Lake Storage Gen2. Data analysts need to run ad-hoc SQL queries on this data to analyze user behavior patterns. The queries are complex, involve joins across multiple files, and the analysts prefer not to move the data into a separate store. 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 Synapse Serverless SQL pool
Azure Synapse Serverless SQL pool is the correct choice because it allows analysts to run T-SQL queries directly against CSV files stored in Azure Data Lake Storage Gen2 without moving the data. It uses a distributed query engine to process complex joins across multiple files, making it ideal for ad-hoc analytics on large-scale log data.
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 Data Factory
Why it's wrong here
Incorrect. Azure Data Factory is used for data integration and orchestration, not for running ad-hoc SQL queries on data.
- ✓
Azure Synapse Serverless SQL pool
Why this is correct
Correct. Serverless SQL pool in Azure Synapse allows you to query data in Data Lake Storage using T-SQL without moving it, enabling ad-hoc analysis with minimal setup.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure SQL Database
Why it's wrong here
Incorrect. Azure SQL Database requires data to be loaded into the database first, which involves data movement and additional costs, contrary to the requirement of keeping data in place.
- ✗
Azure HDInsight
Why it's wrong here
Incorrect. HDInsight is a managed Hadoop/Spark service that can query data in Data Lake, but it requires using Hive or Spark SQL, not standard T-SQL, and is more complex than needed for simple SQL queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse Azure Data Factory's data movement capabilities with query execution, or assume that any SQL-capable service (like Azure SQL Database) can query external files without data import, but only Synapse Serverless SQL pool provides native, serverless SQL querying over Data Lake Storage.
Detailed technical explanation
How to think about this question
Azure Synapse Serverless SQL pool uses a pay-per-query model, where compute resources are allocated on-demand and billed based on the amount of data processed. It supports OPENROWSET and external tables to query CSV, Parquet, and JSON files directly from Data Lake Storage, leveraging a massively parallel processing (MPP) architecture for efficient joins across files. In real-world scenarios, this eliminates the latency and cost of data ingestion while enabling complex analytical queries on petabyte-scale data.
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.
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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 Serverless SQL pool — Azure Synapse Serverless SQL pool is the correct choice because it allows analysts to run T-SQL queries directly against CSV files stored in Azure Data Lake Storage Gen2 without moving the data. It uses a distributed query engine to process complex joins across multiple files, making it ideal for ad-hoc analytics on large-scale log data.
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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