DP-203 Design and implement data storage Practice Question
You are using Azure Synapse Analytics serverless SQL pool to query data in Parquet files stored in Azure Data Lake Storage Gen2. The queries are slow when filtering on a date column. You need to improve query performance without changing the data structure. What should you do?
⚠ Common exam trap
Test-takers frequently assume serverless SQL pool supports materialized views or SLO adjustments like dedicated SQL pool, but serverless SQL pool lacks these features and relies on data layout optimizations such as partitioning for performance.
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
✓
Partition the Parquet files into folders by date
D is correct because partitioning Parquet files into folders by date enables partition elimination in Azure Synapse serverless SQL pool. When queries filter on the date column, the engine can prune entire folders from the scan, reading only the relevant Parquet files. This reduces I/O and improves performance without altering the data structure or format.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create materialized views in the serverless SQL pool
Why it's wrong here
Materialized views are not supported in serverless SQL pool.
- ✗
Increase the service level objective (SLO) of the serverless SQL pool
Why it's wrong here
Serverless SQL pool does not have an SLO setting; it scales automatically based on workload.
- ✗
Convert the Parquet files to CSV format
Why it's wrong here
Parquet is a columnar format optimized for analytics; converting to CSV would likely degrade performance.
- ✓
Partition the Parquet files into folders by date
Why this is correct
Partition elimination allows the serverless SQL pool to read only relevant folders, improving performance.
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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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.