AZ-204 Develop Azure compute solutions Practice Question
You are building a real-time dashboard that displays data from Azure Event Hubs. You need to aggregate events over a one-minute window and update the dashboard every minute. Which Azure service should you use?
⚠ Common exam trap
It's easy for candidates to confuse Azure Stream Analytics with Azure Data Factory, mistakenly thinking Data Factory can handle real-time streaming when it is actually designed for batch-oriented data movement and transformation.
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
Azure Stream Analytics is the correct choice because it is designed for real-time stream processing, allowing you to aggregate events from Azure Event Hubs over a one-minute tumbling window and output results to a dashboard or sink. It natively supports windowing functions (e.g., TumblingWindow, HoppingWindow) and can handle high-throughput, low-latency data streams, making it ideal for updating a dashboard every minute.
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
Why this is correct
Azure Stream Analytics is purpose-built for real-time analytics on streaming data, making it the ideal choice for a real-time dashboard. It allows for continuous data ingestion, transformation, and aggregation from sources like Azure Event Hubs or IoT Hubs using a SQL-like query language. This service is optimized for low-latency processing, enabling immediate insights and visualization of live data streams.
- ✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is primarily an orchestration service for building and scheduling data-driven workflows, commonly referred to as ETL (Extract, Transform, Load) pipelines. It excels at moving and transforming large volumes of data in a batch-oriented manner, often on a scheduled basis, rather than processing continuous, high-velocity data streams in real-time. Its design is not optimized for the immediate, sub-second latency required by a real-time dashboard.
- ✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services is a platform for creating and managing analytical data models, typically tabular or multidimensional, which serve as semantic layers for business intelligence and reporting tools. It operates on pre-processed, structured data, allowing users to perform complex analytical queries with high performance. However, it is not designed to ingest, process, or transform raw, incoming data streams in real-time for live dashboard updates.
- ✗
Azure Logic Apps
Why it's wrong here
Azure Logic Apps is a serverless platform for building automated workflows and integrating applications, data, and services across various environments. While it can react to events and trigger actions, it is fundamentally a workflow engine designed for discrete event processing and task automation, not for high-throughput, continuous stream processing and complex aggregations required for a real-time dashboard. Its architecture is not optimized for the continuous querying and transformation of massive data streams.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-204 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 AZ-204 exam.