Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A company needs to build a centralized analytics platform that can query both structured data in a relational data warehouse and unstructured data in a data lake using a single SQL-based interface. They want to minimize data movement and use a serverless, on-demand compute model for ad-hoc queries. Which Azure service should they use?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
A. Azure SQL Database
Azure SQL Database is a fully managed relational database service, but it cannot directly query data in a data lake without data movement, and it is not serverless in the sense of pay-per-query.
B
Best answer
B. Azure Synapse Serverless SQL pool
Azure Synapse Serverless SQL pool provides a serverless, on-demand query interface that can read data from various sources in the data lake using T-SQL, without data movement or provisioning.
C
Distractor review
C. Azure HDInsight
Azure HDInsight is a managed big data platform (Hadoop, Spark, etc.) that requires provisioning clusters and is not a serverless SQL query service for ad-hoc analysis.
D
Distractor review
D. Azure Analysis Services
Azure Analysis Services is an enterprise-scale analytics engine for creating semantic models and does not directly query data lake files with T-SQL in a serverless manner.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
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.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
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 allows querying data stored in a data lake (e.g., Azure Data Lake Storage Gen2) using T-SQL without provisioning any dedicated compute resources. It is a serverless, on-demand service that charges per query, making it ideal for ad-hoc analytics on data lakes. Azure SQL Database is relational only, HDInsight is a managed Hadoop cluster (not serverless SQL), and Azure Analysis Services is for semantic models, not direct data lake querying.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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