DP-900 Describe an analytics workload on Azure Practice Question
A retail company collects sales data from multiple stores. Data is ingested into Azure Data Lake Storage Gen2 as CSV files. The data team needs to run ad-hoc SQL queries on this data without moving it, and they want to pay only for the amount of data processed. They also need to integrate with Power BI for visualization. Which Azure service should they use?
⚠ Common exam trap
Many exam-takers confuse Azure Synapse Serverless SQL pool with Azure Synapse Analytics dedicated SQL pool, mistakenly thinking both require provisioning and pay for compute, or they overlook that Azure Data Lake Analytics is deprecated and not the correct service for ad-hoc SQL queries on data lakes.
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 (option D) is correct because it allows querying data directly from Azure Data Lake Storage Gen2 using T-SQL without moving the data, and it uses a pay-per-query model where you are billed only for the amount of data processed. It also integrates seamlessly with Power BI for visualization, making it ideal for ad-hoc SQL queries on CSV files.
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
Dedicated SQL pool in Azure Synapse requires always-on provisioned compute with a fixed cost, making it unsuitable for ad-hoc, on-demand querying of CSV files in a data lake. It is optimized for large-scale, predictable data warehousing workloads using massively parallel processing and columnar stores, but for occasional interactive queries, it incurs unnecessary expense and management overhead. Because the question describes immediately querying collected sales data without provisioning a persistent cluster, the serverless alternative is the appropriate choice.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is a fully managed relational database service designed for online transaction processing (OLTP), with row-based storage and indexes optimized for point lookups and updates. It does not natively support querying external files such as CSV stored in Azure Data Lake Storage Gen2 using standard T-SQL across diverse data lake schemas; instead, data must be ingested into tables first. While Azure Synapse offers the ability to define external tables against data lake files, Azure SQL Database lacks that capability, making it the wrong tool for directly analyzing raw sales CSVs.
- ✗
Azure Data Lake Analytics
Why it's wrong here
Azure Data Lake Analytics is an on-demand analytics service that processes files in Azure Data Lake Storage using U-SQL, a hybrid language combining SQL with C# for custom logic. Although it also uses pay-per-query pricing, U-SQL is not standard T-SQL and the service has been planned for retirement, with its capabilities increasingly subsumed by Azure Synapse Serverless SQL pool. For a user who expects to run familiar relational SQL and integrate directly with Power BI, Data Lake Analytics adds unnecessary language complexity and is a legacy approach.
- ✓
Azure Synapse Serverless SQL pool
Why this is correct
Azure Synapse Serverless SQL pool lets you run on-demand T-SQL queries directly against files in Azure Data Lake Storage Gen2, including CSV, without provisioning any compute. You pay only for the amount of data scanned by each query, making it ideal for ad-hoc exploration of sales data from multiple stores, and it integrates natively with Power BI through built-in endpoints. Because it reads files in-place using standard SQL and requires no cluster setup, it directly matches the requirement of querying collected data for interactive analysis.
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
Serverless SQL pool
Serverless SQL pool is an on-demand, pay-per-query analytics service in Azure that lets you query data stored in data lakes without provisioning or managing any dedicated infrastructure.
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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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.