DP-203 Develop data processing Practice Question
You are building a real-time dashboard to monitor user activity on a website. The data is ingested via Azure Event Hubs and must be aggregated every minute with a 30-second late-arrival tolerance. The aggregated results should be stored in Azure Cosmos DB for low-latency reads. Which Azure service should you use to perform the windowed aggregation?
⚠ Common exam trap
Candidates often confuse tumbling windows (fixed, non-overlapping) with sliding windows (continuous, overlapping) or assume that any compute service (like Functions or Databricks) can easily replicate Stream Analytics' built-in windowing and late-arrival handling, ignoring the complexity of state management and exactly-once semantics.
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
✓
Azure Stream Analytics with a tumbling window of 1 minute and a late-arrival policy of 30 seconds.
Azure Stream Analytics is the correct choice because it natively supports windowed aggregations (tumbling, hopping, sliding, session) and allows you to define a late-arrival policy to handle out-of-order events. A tumbling window of 1 minute with a late-arrival tolerance of 30 seconds meets the requirement exactly, and the output can be directly written to Azure Cosmos DB for low-latency reads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure Stream Analytics with a tumbling window of 1 minute and a late-arrival policy of 30 seconds.
Why this is correct
Stream Analytics provides built-in windowing functions and late-arrival handling, perfect for this scenario.
- ✗
Azure Functions triggered by Event Hubs to aggregate data and write to Cosmos DB.
Why it's wrong here
Azure Functions doesn't natively support windowed aggregation; you would need to implement state management manually.
- ✗
Azure Databricks with structured streaming and a sliding window.
Why it's wrong here
While capable, it introduces unnecessary complexity and cost for a simple aggregation.
- ✗
Azure Analysis Services to process streaming data directly from Event Hubs.
Why it's wrong here
Analysis Services is a tabular model engine, not a streaming processor.
Go deeper
Related to this question
About these practice questions
This DP-203 question is part of Courseiva's 760-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam 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.