Secure, monitor, and optimize data storage and data processing →mediumMultiple ChoiceObjective-mapped
DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are using Azure Data Factory to load data from an on-premises SQL Server to Azure Synapse Analytics. The data size is 500 GB, and you need to minimize the load time. The network bandwidth is limited. Which approach should you use?
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 a self-hosted integration runtime and stage the data in Azure Blob Storage before loading to Synapse.
Using a self-hosted integration runtime with staging via Azure Blob Storage allows you to stage the data in Azure before loading to Synapse, which is faster over limited bandwidth. Option A (copy directly) is slower due to the bandwidth limitation. Option C (Azure ExpressRoute) requires additional setup and cost, but the question asks for the approach that minimizes load time with limited bandwidth, and staging is the most efficient. Option D (Azure Data Lake Storage) is similar to staging but not as optimized for the scenario.
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 a self-hosted integration runtime and copy directly to Synapse.
Why it's wrong here
Direct copy over limited bandwidth is slow.
- ✓
Use a self-hosted integration runtime and stage the data in Azure Blob Storage before loading to Synapse.
Why this is correct
Staging improves performance by splitting the copy into two phases.
- ✗
Use Azure ExpressRoute to improve network bandwidth.
Why it's wrong here
ExpressRoute may not be feasible or cost-effective.
- ✗
Use an Azure integration runtime and copy to Azure Data Lake Storage, then to Synapse.
Why it's wrong here
Azure IR cannot access on-premises directly.
Visual reference
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Introduction to Azure Data Engineering
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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.
About these practice questions
Courseiva writes every DP-203 question from scratch — 760 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
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.