DP-203 Optimize ADLS Gen2 for Synapse SQL Practice Question
You are designing a data lake architecture using Azure Data Lake Storage Gen2. You need to optimize query performance for Azure Synapse Analytics serverless SQL. Which three design considerations should you follow? (Choose three.)
⚠ Common exam trap
It's easy for candidates to confuse file size optimization with parallelism, assuming smaller files increase parallelism, but in serverless SQL, too many small files cause excessive metadata requests and reduce throughput, while larger files enable better batch processing.
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
✓
Store data in Parquet format
Parquet is a columnar storage format that reduces I/O by reading only the columns needed for a query, which significantly improves performance in Azure Synapse serverless SQL. It also supports efficient compression and encoding schemes, making it ideal for analytical workloads on Azure Data Lake Storage Gen2.
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 many small files (under 64 MB) to increase parallelism
Why it's wrong here
Small files cause overhead; larger files (128 MB+) are recommended.
- ✗
Store data in nested folder structures for better organization
Why it's wrong here
Deeply nested folders increase file listing time, impacting performance.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The DP-203 exam frequently reuses these exact scenarios with slightly different constraints.
✓Store data in Parquet formatCorrect answer▾
✗Use many small files (under 64 MB) to increase parallelismWrong answer — click to see why▾
Why this is wrong here
Small files cause overhead; larger files (128 MB+) are recommended.
✗Store data in nested folder structures for better organizationWrong answer — click to see why▾
Why this is wrong here
Deeply nested folders increase file listing time, impacting performance.
Analysis generated from the official DP-203blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
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 |
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About these practice questions
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.