DP-203 Develop data processing Practice Question
You have an Azure Data Factory pipeline that must copy data from an on-premises Oracle database to Azure Blob Storage every night. The on-premises server cannot accept inbound connections, and no VPN or ExpressRoute is available. You need to enable connectivity with minimal administrative overhead. What should you deploy?
⚠ Common exam trap
The trap here is assuming network-level connectivity such as VPN or ExpressRoute is required for on-premises access, when the self-hosted integration runtime already solves it with outbound-only connections.
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
✓
A self-hosted integration runtime installed on a machine in the on-premises network.
The self-hosted integration runtime is the standard Azure Data Factory mechanism for reaching on-premises data sources when inbound connectivity is not possible. It initiates outbound HTTPS connections to the Data Factory service, so it works without VPN, ExpressRoute, or firewall changes. It also supports the Oracle connector and Blob Storage sink required by this nightly copy pipeline.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
An Azure VPN Gateway with a site-to-site connection to the on-premises network.
Why it's wrong here
A site-to-site VPN Gateway provides network-level connectivity but requires configuration of on-premises VPN devices, routing, and firewall rules, which is significant administrative overhead. The scenario explicitly states no VPN or ExpressRoute is available, so this option contradicts the stated constraints. It is also unnecessary because the self-hosted integration runtime already solves outbound-only connectivity.
- ✓
A self-hosted integration runtime installed on a machine in the on-premises network.
Why this is correct
The self-hosted integration runtime is designed exactly for this case: it runs on an on-premises machine and makes outbound connections to Azure Data Factory over HTTPS, so no inbound firewall rules or VPN are required. It supports Oracle as a source and Blob Storage as a sink, and installation is lightweight, matching the minimal-overhead requirement.
- ✗
An Azure ExpressRoute circuit with private peering to the on-premises datacenter.
Why it's wrong here
ExpressRoute provides private, high-bandwidth connectivity but requires a connectivity provider, physical cross-connections, and significant provisioning time and cost. The scenario states no ExpressRoute is available, and the requirement is minimal administrative overhead for a nightly copy. ExpressRoute is overkill and does not fit the stated constraints.
- ✗
An Azure Integration Runtime with a managed virtual network and private endpoints to the Oracle server.
Why it's wrong here
Managed virtual networks and private endpoints allow Azure-hosted integration runtimes to reach private endpoints inside Azure, but they cannot reach an on-premises Oracle server that has no inbound connectivity. Private endpoints terminate inside Azure virtual networks, not on-premises. This option therefore cannot establish the required path from Data Factory to the on-premises database.
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
Implement Azure Data Factory Pipelines
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
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.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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.