The answer is to use Azure Stream Analytics to output to both Power BI and Data Lake Storage Gen2. This is correct because Stream Analytics natively supports multiple outputs from a single streaming job, allowing you to route the same streaming data to a real-time dashboard via Power BI while simultaneously landing it in Data Lake Storage for historical analysis—all without custom code or additional orchestration. On the DP-203 exam, this scenario tests your understanding of minimizing operational overhead in a streaming architecture; a common trap is choosing Azure Databricks or Azure Functions, which introduce cluster management or custom batching logic that increase complexity. Remember the key pattern: one Stream Analytics job, two outputs—Power BI for the live view, Data Lake for the deep dive. A helpful memory tip is "Stream to two: live and review."
DP-203 Develop data processing Practice Question
This DP-203 practice question tests your understanding of develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are designing a data processing solution for a healthcare organization. The solution must process streaming data from IoT devices and store it in Azure Data Lake Storage Gen2. The data must be available for both real-time dashboards and historical analysis. You need to minimize operational overhead. What should you do?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Azure Stream Analytics to output to both Power BI and Data Lake Storage
Using Azure Stream Analytics with output to both Power BI (real-time) and Data Lake Storage (historical) is a common pattern with minimal overhead. Option A is wrong because Azure Functions would require custom code for batching. Option B is wrong because Event Hubs doesn't provide real-time dashboards. Option C is wrong because Azure Databricks would require cluster management.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Ingest data via Azure Functions and write to Data Lake Storage; use Power BI to query Data Lake
Why it's wrong here
Azure Functions add operational overhead and latency for real-time dashboards.
✓
Use Azure Stream Analytics to output to both Power BI and Data Lake Storage
Why this is correct
Stream Analytics is serverless, supports real-time output to Power BI and batch writes to Data Lake.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
✗
Use Azure Databricks with Structured Streaming to write to Data Lake Storage and use Power BI DirectQuery
Why it's wrong here
Operational overhead of managing clusters.
✗
Ingest data to Azure Event Hubs, then use Event Hubs Capture to store in Data Lake Storage; use Power BI with Event Hubs
Why it's wrong here
Event Hubs Capture is batch, not real-time for dashboards.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DP-203 NAT questions on configuration and troubleshooting.
Develop data processing — This question tests Develop data processing — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Use Azure Stream Analytics to output to both Power BI and Data Lake Storage — Using Azure Stream Analytics with output to both Power BI (real-time) and Data Lake Storage (historical) is a common pattern with minimal overhead. Option A is wrong because Azure Functions would require custom code for batching. Option B is wrong because Event Hubs doesn't provide real-time dashboards. Option C is wrong because Azure Databricks would require cluster management.
What should I do if I get this DP-203 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DP-203 NAT questions on configuration and troubleshooting.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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