DP-900 Describe an analytics workload on Azure Practice Question
A retail company stores historical sales data from multiple stores in Azure Data Lake Storage Gen2 as CSV files. They need to run complex SQL queries that join and aggregate data across multiple files to generate weekly sales reports. They want a serverless query service that can directly query the data in the lake without loading it into a separate database. Which Azure service should they use?
⚠ Common exam trap
Candidates often confuse Azure Synapse Serverless SQL pool with Azure SQL Database, assuming both can query data lakes directly, but Azure SQL Database requires data to be imported first, while the serverless SQL pool is purpose-built for on-demand querying of data lake files.
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 provides a serverless, on-demand SQL query engine that can directly query CSV files stored in Azure Data Lake Storage Gen2 using T-SQL syntax. It supports complex joins and aggregations across multiple files without requiring data movement or loading into a separate database, making it ideal for ad-hoc reporting on data lakes.
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 is a managed relational database that stores data in its own internal table structures; it is not a file-parsing query engine for Azure Data Lake Storage. Although you can load data into it with tools like Azure Data Factory or the COPY statement, you cannot point T-SQL directly at a folder of Parquet or CSV files in a data lake. That architecture requires a compute layer designed for external data sources, which Azure SQL Database does not provide.
- ✓
Azure Synapse Serverless SQL pool
Why this is correct
Azure Synapse Serverless SQL pool enables serverless querying of data stored in Azure Data Lake Storage (Parquet, CSV, etc.) without needing to load data into a separate store. It scales automatically and charges per query.
- ✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics is built for continuous, real-time event processing—it reads data on the move from sources like Event Hubs or IoT Hub and writes results downstream. It is not an interactive query engine for historical files, and its SQL-like language is defined in a job that runs indefinitely rather than a one-off SELECT against a static data lake. For ad-hoc analysis of stored Parquet or CSV files, you want an on-demand compute service, not a streaming pipeline.
- ✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is an orchestration and data integration service, not a query engine. It can copy files, call Azure Databricks or Synapse pipelines, and run stored procedures, but it has no endpoint that accepts an ad-hoc SQL query and returns results from data lake files. Analysts would use Data Factory to prepare or load data, whereas Azure Synapse Serverless SQL pool directly executes T-SQL on the files themselves.
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
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Data lake
A data lake is a centralized storage repository that holds vast amounts of raw data in its native format until it is needed for analysis.
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