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 data analyst needs to query large datasets stored as Parquet files in Azure Data Lake Storage Gen2. The queries are ad-hoc and infrequent. The analyst wants to run SQL queries directly on the data without creating any storage or compute infrastructure, and only pay for the amount of data processed. They also need to create T-SQL views to simplify queries for Power BI reports. Which Azure service should they use?
Why wrong: Azure SQL Database requires a provisioned database and does not directly query external files in ADLS Gen2 without additional tools like PolyBase.
B
Azure Synapse Serverless SQL pool
Correct. It is a serverless query service that can directly query Parquet files in ADLS Gen2 using T-SQL, charges per query, and supports views.
C
Azure HDInsight with Spark
Why wrong: HDInsight requires a managed cluster, incurs compute cost even when idle, and does not provide a serverless pay-per-query model.
D
Azure Databricks
Why wrong: Databricks requires a cluster to run, even if auto-scaling, and its primary interface is Spark (not T-SQL). It does not offer a pure serverless SQL query experience for ad-hoc queries.
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 querying data directly from Azure Data Lake Storage Gen2 using T-SQL without provisioning any compute or storage infrastructure. It supports ad-hoc, infrequent queries with a pay-per-query pricing model based on the amount of data processed, and it enables the creation of T-SQL views that can be used directly by Power BI for reporting.
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 requires a provisioned database and does not directly query external files in ADLS Gen2 without additional tools like PolyBase.
✓
Azure Synapse Serverless SQL pool
Why this is correct
Correct. It is a serverless query service that can directly query Parquet files in ADLS Gen2 using T-SQL, charges per query, and supports views.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure HDInsight with Spark
Why it's wrong here
HDInsight requires a managed cluster, incurs compute cost even when idle, and does not provide a serverless pay-per-query model.
✗
Azure Databricks
Why it's wrong here
Databricks requires a cluster to run, even if auto-scaling, and its primary interface is Spark (not T-SQL). It does not offer a pure serverless SQL query experience for ad-hoc queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'serverless' with 'no infrastructure at all' and incorrectly choose Azure SQL Database or HDInsight, failing to recognize that Synapse Serverless SQL pool specifically provides a T-SQL interface over data lake storage with a pay-per-query model, while the other options require persistent compute resources.
Detailed technical explanation
How to think about this question
Azure Synapse Serverless SQL pool uses a distributed query engine that reads Parquet files directly from Azure Data Lake Storage Gen2 via the OPENROWSET function or external tables, leveraging columnar storage and predicate pushdown to minimize data scanned. Under the hood, it dynamically allocates compute resources per query and charges based on the amount of data processed (in terabytes), making it cost-effective for sporadic workloads. T-SQL views created in the serverless pool are metadata-only objects that do not store data, allowing Power BI to issue queries that are executed on-demand against the underlying files.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 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 querying data directly from Azure Data Lake Storage Gen2 using T-SQL without provisioning any compute or storage infrastructure. It supports ad-hoc, infrequent queries with a pay-per-query pricing model based on the amount of data processed, and it enables the creation of T-SQL views that can be used directly by Power BI for reporting.
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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