DP-203 Develop data processing Practice Question
Which TWO are valid ways to process data in Azure Synapse Analytics?
⚠ Common exam trap
It's easy for candidates to confuse general Azure services (Logic Apps, Functions, Power BI) with native Synapse Analytics processing capabilities, forgetting that only Synapse SQL and Synapse Spark are first-class compute engines within the service.
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
✓
Use Synapse SQL pool to run T-SQL queries.
Synapse SQL pool (formerly SQL DW) is a dedicated or serverless SQL engine within Azure Synapse Analytics that allows you to run T-SQL queries for data transformation, loading, and querying. It is a first-class compute resource designed for large-scale data warehousing workloads, making T-SQL queries a valid and primary method for processing data in Synapse.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Logic Apps to run data transformations.
Why it's wrong here
Logic Apps are for orchestration and workflow, not heavy data processing.
- ✗
Use Azure Functions to process data in a serverless manner.
Why it's wrong here
Azure Functions can process data but are not a native Synapse processing engine.
- ✓
Use Synapse SQL pool to run T-SQL queries.
Why this is correct
Synapse SQL pool provides distributed query processing.
- ✗
Use Power BI to transform data.
Why it's wrong here
Power BI is for analytics and visualization, not data transformation.
- ✓
Use Synapse Spark notebooks to run Scala code.
Why this is correct
Synapse Spark is a built-in processing engine.
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
Introduction to Azure Data Engineering
Key term
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
Key term
Data Transformation Pipelines
Data transformation pipelines are automated sequences of steps that take raw data from a source, clean and reshape it into a usable format, and then load it into a destination for analysis or storage.
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This DP-203 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-203 exam.