Azure Synapse Serverless SQL Pool for Ad-Hoc Queries on Data Lake
A data analyst needs to run ad-hoc SQL queries on petabytes of data stored as Parquet files in Azure Data Lake Storage Gen2. The queries are infrequent but must return results within seconds. The analyst wants to pay only for the amount of data processed and does not want to manage any compute infrastructure. Additionally, they need to create views to simplify future reporting in Power BI. Which Azure service should they use?
Quick Answer
The answer is Azure Synapse Serverless SQL pool, which is the correct choice because it enables ad-hoc queries on petabytes of Parquet files in Azure Data Lake Storage Gen2 using standard T-SQL without any infrastructure management. This service operates on a pay-per-query model, charging only for the data scanned per query, and it supports creating T-SQL views that Power BI can directly consume for reporting. On the DP-900 exam, this scenario tests your understanding of the serverless versus dedicated compute models in Azure Synapse Analytics, often appearing as a trap where candidates mistakenly choose Azure SQL Database or Azure Databricks—both of which require provisioning or cluster management. The key differentiator is the combination of zero infrastructure, pay-per-query billing, and view creation for Power BI. Memory tip: think “Serverless = no servers to manage, just SQL on the lake, pay per byte.”
⚠ Common exam trap
Test-takers frequently confuse 'serverless' with 'Dedicated SQL pool' (Option C) because both are part of Azure Synapse Analytics, but Dedicated SQL pool requires provisioning and pays for reserved compute, not data processed.
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 is the correct choice because it allows querying petabytes of data in Azure Data Lake Storage Gen2 using standard T-SQL without provisioning any compute infrastructure. It charges only for the amount of data processed per query (pay-per-query model) and supports creating views for Power BI reporting, meeting all stated requirements.
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 Serverless SQL pool
Why this is correct
Serverless SQL pool is designed for on-demand querying of data in a data lake, with pay-per-query pricing and support for T-SQL views, making it ideal for this scenario.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is a fully managed relational database, not designed for querying external data in a data lake. It requires provisioning compute and storage, and costs are based on reserved resources, not per-query.
- ✗
Azure Synapse Dedicated SQL pool
Why it's wrong here
Dedicated SQL pool requires provisioning and paying for dedicated compute resources (even when idle) and is not pay-per-query. It is more suited for heavy, predictable workloads.
- ✗
Azure HDInsight with Spark
Why it's wrong here
HDInsight is a managed cluster service that requires provisioning and managing clusters. It is not serverless and does not have pay-per-query pricing for SQL queries.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data Lake Storage Gen2
Data Lake Storage Gen2 is a cloud-based storage service that combines a scalable data lake with enterprise-grade file system capabilities for big data analytics.
Key term
Power BI
Power BI is a Microsoft business analytics tool that transforms raw data into interactive visual reports and dashboards for informed decision-making.
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Same concept, more angles
5 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 petabytes of log data stored as Parquet files in Azure Data Lake Storage Gen2. The queries join multiple tables and require high concurrency from multiple analysts. The solution should minimize cost by only paying for queries executed. Which Azure service should they use?
hard- ✓ A.Azure Synapse Serverless SQL pool
- B.Azure Synapse Dedicated SQL pool
- C.Azure HDInsight with Spark
- D.Azure Databricks
Why A: Azure Synapse Serverless SQL pool is the correct choice because it allows running ad-hoc T-SQL queries directly on Parquet files in Azure Data Lake Storage Gen2 without provisioning any infrastructure. It uses a pay-per-query billing model, making it cost-effective for sporadic, high-concurrency workloads where you only want to pay for the compute resources consumed during query execution.
Variation 2. A data analyst needs to run interactive SQL queries on a large dataset stored as CSV files in Azure Blob Storage. The analyst wants to explore the data using T-SQL without loading the data into a database. Which Azure service should they use?
medium- A.Azure SQL Database
- ✓ B.Azure Synapse Serverless SQL pool
- C.Azure Data Factory
- D.Azure Stream Analytics
Why B: Azure Synapse Serverless SQL pool is correct because it allows you to run interactive T-SQL queries directly against CSV files in Azure Blob Storage without loading the data into a database. It uses a pay-per-query model and leverages the OPENROWSET function to query external data in place, making it ideal for ad-hoc exploration of large datasets.
Variation 3. A data analyst needs to run ad-hoc SQL queries on large datasets stored as Parquet files in Azure Data Lake Storage Gen2. The queries are infrequent and the data volume varies. The analyst wants to pay only for the amount of data processed per query and does not want to manage any infrastructure. They also need to create views in T-SQL to simplify queries for Power BI reports. Which Azure service should they use?
hard- ✓ A.Azure Synapse Serverless SQL pool
- B.Azure Data Lake Analytics
- C.Azure HDInsight
- D.Azure Databricks
Why A: Azure Synapse Serverless SQL pool is the correct choice because it allows running ad-hoc T-SQL queries directly on Parquet files in Azure Data Lake Storage Gen2 without provisioning any infrastructure. It uses a pay-per-query model, charging only for the amount of data processed, and supports creating T-SQL views that can be used directly by Power BI for simplified reporting.
Variation 4. 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?
medium- A.Azure SQL Database
- ✓ B.Azure Synapse Serverless SQL pool
- C.Azure HDInsight with Spark
- D.Azure Databricks
Why B: Azure Synapse Serverless SQL pool (Option B) 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. In contrast, Option A (Azure SQL Database) requires provisioning a database with compute resources, incurring continuous costs. Option C (Azure HDInsight with Spark) requires a persistent cluster and is not optimized for infrequent ad-hoc queries. Option D (Azure Databricks) also requires compute resources and is not a pay-per-query service.
Variation 5. A data analyst needs to run ad-hoc SQL queries on petabytes of Parquet files stored in Azure Data Lake Storage Gen2. The queries are infrequent and highly selective. The analyst wants to pay only for the data scanned by each query and does not want to provision any compute resources. They also need to create views to simplify future queries for other analysts. Which Azure service should they use?
medium- A.Azure Data Factory
- ✓ B.Azure Synapse Serverless SQL pool
- C.Azure Synapse Dedicated SQL pool
- D.Azure Databricks
Why B: Azure Synapse Serverless SQL pool (correct answer) is a pay-per-query service that charges only for the data scanned, requires no provisioning of compute resources, and supports creating views over external data in Azure Data Lake Storage Gen2. It uses T-SQL to query Parquet files directly, making it ideal for infrequent, highly selective ad-hoc queries without managing infrastructure.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.