Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A marketing company stores years of historical campaign data in Azure Data Lake Storage Gen2 as Parquet files. Data analysts need to run complex SQL queries over this data to identify trends, and they want to visualize results in Power BI dashboards. The company wants to avoid moving data into a separate database to minimize duplication and latency. Which Azure service should they use to query the data directly in the data lake?
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
Azure Data Factory
Azure Data Factory is an ETL and orchestration service. It does not provide a direct SQL query interface over data in a data lake; it moves or transforms data but does not serve interactive queries.
B
Best answer
Azure Synapse Serverless SQL pool
Serverless SQL pool (part of Azure Synapse Analytics) enables querying data directly from Azure Data Lake Storage using standard T-SQL. It is serverless (no infrastructure to manage) and perfect for ad-hoc analytics integration with Power BI.
C
Distractor review
Azure Databricks
Azure Databricks provides a Spark-based analytics platform. While it can query Parquet files, it requires using Spark SQL or notebooks, not standard T-SQL. It also involves cluster management and is not serverless by default.
D
Distractor review
Azure HDInsight
Azure HDInsight is a managed Hadoop/Spark service. It can query data in a data lake but requires provisioning a cluster, is more complex to manage, and is not ideal for simple ad-hoc SQL queries that integrate directly with Power BI.
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: Azure Synapse Serverless SQL pool — Azure Synapse Serverless SQL pool (formerly SQL on-demand) allows you to run T-SQL queries directly on files in a data lake without loading the data into a separate store. It is ideal for ad-hoc querying over Parquet, CSV, and other formats, and integrates with Power BI. Azure Data Factory is an orchestration service, not a query engine. Azure Databricks uses Spark, not T-SQL directly. Azure HDInsight runs Hadoop clusters which require more management and are not serverless.
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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