Question 643 of 982

Describe an analytics workload on Azure →mediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is Azure Synapse Serverless SQL pool because it enables ad-hoc queries on terabytes of CSV files in Azure Data Lake Storage Gen2 without requiring any provisioned compute or infrastructure management. This serverless endpoint processes data on-demand using T-SQL, charging only for the amount of data scanned per query—making it perfect for infrequent, unpredictable workloads where you want pay-per-query billing. On the DP-900 exam, this scenario tests your understanding of the difference between serverless and dedicated SQL pools: a common trap is choosing Azure SQL Database or Azure Databricks, but remember that serverless SQL pool is the only option that eliminates compute management entirely while billing per terabyte processed. A helpful memory tip is "Serverless for sporadic, serverless saves spending"—if the workload is unpredictable and you don’t want to manage resources, think serverless SQL pool for ad-hoc analytics on data lakes.

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 run ad-hoc SQL queries on terabytes of CSV files stored in Azure Data Lake Storage Gen2. The queries are infrequent and unpredictable. The analyst wants to pay only for the amount of data processed by each query, and does not want to manage any compute or storage infrastructure. Which Azure service should they use?

Question 1mediummultiple choice

Full question →

A
Azure Synapse Analytics dedicated SQL pool
Why wrong: A dedicated SQL pool requires provisioning and paying for allocated compute resources continuously, even when no queries are running, which is not cost-effective for infrequent queries.
B
Azure Data Factory
Why wrong: Azure Data Factory is an orchestration service for data pipelines, not a query engine. It cannot directly execute SQL queries against files in the data lake.
C
Azure Synapse Serverless SQL pool
Serverless SQL pool allows on-demand SQL querying of data in the data lake, paying only for the data processed per query, with zero infrastructure management.
D
Azure Analysis Services
Why wrong: Azure Analysis Services is used to build semantic models (tabular or multidimensional) for reporting, not for direct ad-hoc querying of raw files in the data lake.

Full breakdown with real-world context →

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 Serverless SQL pool

Azure Synapse Serverless SQL pool (C) is the correct choice because it allows querying data in Azure Data Lake Storage Gen2 using T-SQL without provisioning any compute resources. It charges per terabyte of data processed, making it ideal for infrequent, unpredictable ad-hoc queries, and it eliminates infrastructure management.

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 dedicated SQL pool
Why it's wrong here
A dedicated SQL pool requires provisioning and paying for allocated compute resources continuously, even when no queries are running, which is not cost-effective for infrequent queries.
✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is an orchestration service for data pipelines, not a query engine. It cannot directly execute SQL queries against files in the data lake.
✓
Azure Synapse Serverless SQL pool
Why this is correct
Serverless SQL pool allows on-demand SQL querying of data in the data lake, paying only for the data processed per query, with zero infrastructure management.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services is used to build semantic models (tabular or multidimensional) for reporting, not for direct ad-hoc querying of raw files in the data lake.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Azure Synapse Serverless SQL pool with Azure Synapse Analytics dedicated SQL pool, assuming both require provisioning compute, but the serverless option is specifically designed for on-demand, pay-per-query workloads with no infrastructure management.

Detailed technical explanation

How to think about this question

Azure Synapse Serverless SQL pool uses a distributed query engine that reads data directly from Azure Data Lake Storage Gen2 via the OPENROWSET or external table syntax, leveraging the storage's hierarchical namespace for efficient partitioning. Under the hood, it uses a pay-per-query model where billing is based on the amount of data scanned (compressed size), with a minimum charge per query, and it automatically scales out compute resources to handle large datasets without user intervention. A real-world scenario is a data analyst needing to quickly explore a 10-TB CSV dataset for a one-time audit, where provisioning a dedicated pool would be cost-prohibitive.

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.

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 Serverless SQL pool — Azure Synapse Serverless SQL pool (C) is the correct choice because it allows querying data in Azure Data Lake Storage Gen2 using T-SQL without provisioning any compute resources. It charges per terabyte of data processed, making it ideal for infrequent, unpredictable ad-hoc queries, and it eliminates infrastructure management.

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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Same concept, more angles

1 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. A data analyst needs to run ad-hoc SQL queries on large volumes of data stored as Parquet files in Azure Data Lake Storage Gen2. The queries are unpredictable, and the analyst wants to pay only for the compute resources consumed by each query. Which Azure Synapse Analytics compute model should be used?

hard

✓ A.Serverless SQL pool
B.Dedicated SQL pool
C.Apache Spark pool
D.Azure Data Explorer pool

Why A: Serverless SQL pool is the correct choice because it allows running ad-hoc SQL queries directly on data in Azure Data Lake Storage Gen2 without provisioning any fixed compute resources. It uses a pay-per-query billing model, charging only for the amount of data processed by each query, which aligns perfectly with the unpredictable query patterns described.

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