- A
Azure Synapse Analytics
Correct. The serverless SQL pool in Azure Synapse Analytics can query Parquet files directly in the data lake, supports T-SQL, and integrates with Power BI.
- B
Azure SQL Database
Why wrong: Azure SQL Database requires data to be loaded into tables, which adds latency and cost. It is not designed for direct querying of data lake files.
- C
Azure Data Factory
Why wrong: Azure Data Factory is an orchestration and ETL service, not an interactive query engine. It can move data but does not support direct SQL queries on data lake files for analytics.
- D
Azure Analysis Services
Why wrong: Azure Analysis Services is used to build semantic models and requires data to be imported from sources. It does not directly query raw files in the data lake.
Quick Answer
The answer is Azure Synapse Analytics, specifically its serverless SQL pool capability. This is the correct choice because it allows business analysts to query Azure Data Lake with serverless SQL directly against Parquet files in Azure Data Lake Storage Gen2 using standard T-SQL, eliminating the need to move or copy data into a separate database. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your understanding of how serverless SQL pools enable on-demand querying of data lakes for ad-hoc analysis and Power BI integration, often contrasting with dedicated SQL pools that require provisioning and storage. A common trap is selecting Azure SQL Database or Azure Databricks, but remember that serverless SQL is purpose-built for querying data in place without infrastructure management. Memory tip: think “serverless = no server to manage, no data to move” — if the question emphasizes avoiding data movement and minimizing latency, serverless SQL pool is your answer.
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 years of historical sales data in Azure Data Lake Storage Gen2 as Parquet files. Business analysts need to run complex SQL queries over this data to identify sales trends, and they want to visualize the results in Power BI dashboards. They prefer to avoid moving data into a separate database to minimize storage costs and latency. Which Azure service should they use to query the data directly in the lake?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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 Analytics
Azure Synapse Analytics provides the serverless SQL pool capability that allows you to query data directly in Azure Data Lake Storage Gen2 using T-SQL without moving or copying the data. This enables business analysts to run complex SQL queries over Parquet files in the lake and connect the results to Power BI for visualization, minimizing storage costs and latency by avoiding a separate database.
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 Synapse Analytics
Why this is correct
Correct. The serverless SQL pool in Azure Synapse Analytics can query Parquet files directly in the data lake, supports T-SQL, and integrates with Power BI.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database requires data to be loaded into tables, which adds latency and cost. It is not designed for direct querying of data lake files.
- ✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is an orchestration and ETL service, not an interactive query engine. It can move data but does not support direct SQL queries on data lake files for analytics.
- ✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services is used to build semantic models and requires data to be imported from sources. It does not directly query raw files in the data lake.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Azure Data Factory as a query service because it can transform data, but it is an orchestration tool, not an interactive SQL query engine for ad-hoc analysis.
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 Azure Storage REST API, leveraging schema inference from the Parquet metadata. It supports T-SQL syntax for complex aggregations and joins, and can push down predicate filtering to the storage layer for performance. In a real-world scenario, analysts can query years of historical sales data partitioned by date in the lake, and Power BI can connect via the Synapse SQL endpoint for near-real-time visualization without data duplication.
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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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 Analytics — Azure Synapse Analytics provides the serverless SQL pool capability that allows you to query data directly in Azure Data Lake Storage Gen2 using T-SQL without moving or copying the data. This enables business analysts to run complex SQL queries over Parquet files in the lake and connect the results to Power BI for visualization, minimizing storage costs and latency by avoiding a separate database.
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.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on DP-900
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. An organization needs to run complex queries on petabytes of data stored in Azure Data Lake Storage. They want to use serverless compute to avoid managing infrastructure. Which Azure service should they use?
easy- A.Azure Analysis Services
- ✓ B.Azure Synapse Serverless SQL pool
- C.Azure HDInsight
- D.Azure SQL Database
Why B: Azure Synapse Serverless SQL pool is the correct choice because it provides serverless compute that can run complex T-SQL queries directly against data stored in Azure Data Lake Storage without requiring any infrastructure management. It uses a pay-per-query billing model and can scale automatically to handle petabytes of data, making it ideal for ad-hoc analytics on large-scale data lakes.
Variation 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?
medium- ✓ A.External tables
- B.Materialized views
- C.Stored procedures
- D.Indexed views
Why A: External tables in Azure Synapse Analytics allow you to query data stored in files (such as CSV in Azure Data Lake Storage Gen2) using T-SQL without loading the data into the database. They use the PolyBase engine to read the files directly, enabling on-the-fly querying of external data sources.
Last reviewed: Jun 11, 2026
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