The answer is Azure Synapse Serverless SQL pool. This service is the correct choice because it enables you to query data in Azure Blob Storage without loading to a database, using standard T-SQL syntax directly against files like CSV, Parquet, or JSON. Instead of provisioning dedicated compute or moving data into a relational store, the serverless SQL pool reads the files on demand and processes queries in a pay-per-query model, making it ideal for ad-hoc exploration of large datasets in a data lake. On the Microsoft Azure Data Fundamentals DP-900 exam, this question tests your understanding of how to separate compute from storage for analytical workloads, often contrasting Synapse Serverless with dedicated SQL pools or Azure Data Lake Analytics. A common trap is choosing Azure SQL Database, which requires data to be loaded first, or Azure Data Factory, which is for orchestration, not direct querying. Remember the memory tip: “Serverless SQL queries files where they lie—no load, no cry.”
DP-900 Describe core data concepts Practice Question
This DP-900 practice question tests your understanding of describe core data concepts. 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.
Your organization has a large dataset of customer transactions stored in Azure Blob Storage as CSV files. You need to run ad-hoc SQL queries on this data without loading it into a database. Which Azure service should you use?
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 allows you to query data directly from files in Azure Blob Storage using standard T-SQL syntax, without needing to load or move the data into a database. It uses a pay-per-query model and supports CSV, Parquet, and JSON formats, making it ideal for ad-hoc analytical queries over large datasets stored in 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 Data Factory
Why it's wrong here
Azure Data Factory is for data movement and orchestration, not ad-hoc querying.
✗
Azure SQL Database
Why it's wrong here
Azure SQL Database requires data to be imported; it cannot directly query external files.
✓
Azure Synapse Serverless SQL pool
Why this is correct
Serverless SQL pool queries data directly from Blob Storage using T-SQL, with no loading required.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services requires data to be loaded into a tabular model.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Data Factory (a data movement/orchestration tool) with a query engine, or assume Azure SQL Database can query external files via PolyBase (which requires loading into external tables, not direct ad-hoc querying).
Detailed technical explanation
How to think about this question
Under the hood, Azure Synapse Serverless SQL pool uses a distributed query engine that reads files via the OPENROWSET function or external tables, leveraging schema inference from file metadata. It supports partitioning elimination and predicate pushdown for performance, and charges based on the amount of data scanned (typically $5 per TB). A real-world scenario is a data analyst needing to quickly explore a year's worth of transaction logs without provisioning a dedicated warehouse, saving both time and cost.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
Describe core data concepts — This question tests Describe core data concepts — 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 allows you to query data directly from files in Azure Blob Storage using standard T-SQL syntax, without needing to load or move the data into a database. It uses a pay-per-query model and supports CSV, Parquet, and JSON formats, making it ideal for ad-hoc analytical queries over large datasets stored in 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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Question Discussion
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