- A
Azure SQL Database
Why wrong: Azure SQL Database is a relational database service that requires data to be imported and stored within it. It does not directly query files in a data lake.
- B
Azure Synapse Serverless SQL pool
Azure Synapse Serverless SQL pool enables serverless querying of data stored in Azure Data Lake Storage (Parquet, CSV, etc.) without needing to load data into a separate store. It scales automatically and charges per query.
- C
Azure Stream Analytics
Why wrong: Azure Stream Analytics is a real-time stream processing service used for analyzing data in motion, not for ad-hoc SQL queries on stored files.
- D
Azure Data Factory
Why wrong: Azure Data Factory is a data integration and orchestration service used to build ETL pipelines, but it does not provide a direct SQL query interface for analyzing data in the lake.
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 company stores historical sales data from multiple stores in Azure Data Lake Storage Gen2 as CSV files. They need to run complex SQL queries that join and aggregate data across multiple files to generate weekly sales reports. They want a serverless query service that can directly query the data in the lake without loading it into a separate database. 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 provides a serverless, on-demand SQL query engine that can directly query CSV files stored in Azure Data Lake Storage Gen2 using T-SQL syntax. It supports complex joins and aggregations across multiple files without requiring data movement or loading into a separate database, making it ideal for ad-hoc reporting on data lakes.
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 SQL Database
Why it's wrong here
Azure SQL Database is a relational database service that requires data to be imported and stored within it. It does not directly query files in a data lake.
- ✓
Azure Synapse Serverless SQL pool
Why this is correct
Azure Synapse Serverless SQL pool enables serverless querying of data stored in Azure Data Lake Storage (Parquet, CSV, etc.) without needing to load data into a separate store. It scales automatically and charges per query.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics is a real-time stream processing service used for analyzing data in motion, not for ad-hoc SQL queries on stored files.
- ✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is a data integration and orchestration service used to build ETL pipelines, but it does not provide a direct SQL query interface for analyzing data in the lake.
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 can query data lakes directly, but Azure SQL Database requires data to be imported first, while the serverless SQL pool is purpose-built for on-demand querying of data lake files.
Detailed technical explanation
How to think about this question
Under the hood, Azure Synapse Serverless SQL pool uses a distributed query engine that reads data directly from the data lake via the OPENROWSET function or external tables, leveraging the T-SQL language. It supports partitioning elimination and predicate pushdown to optimize performance when querying large CSV datasets, and it can infer schemas automatically from file headers. A real-world scenario where this matters is when a company needs to run weekly sales reports across hundreds of CSV files without provisioning dedicated compute resources, paying only for the data scanned.
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 provides a serverless, on-demand SQL query engine that can directly query CSV files stored in Azure Data Lake Storage Gen2 using T-SQL syntax. It supports complex joins and aggregations across multiple files without requiring data movement or loading into a separate database, making it ideal for ad-hoc reporting on data lakes.
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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