The correct combination is Azure Stream Analytics and Power BI. This is because Stream Analytics serves as a real-time event processing engine that ingests IoT sensor data from sources like Azure Event Hubs, applies SQL-based queries to detect patterns or anomalies, and outputs the results directly to Power BI for live dashboard visualization, enabling sub-second latency essential for a real-time IoT dashboard. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your understanding of Azure’s real-time analytics services versus batch processing tools like Azure Synapse Analytics; a common trap is choosing Azure Data Lake Storage or Azure SQL Database, which are not designed for streaming ingestion and live dashboard refresh. To remember this pairing, think of Stream Analytics as the “engine” that processes the data stream and Power BI as the “dashboard” that displays it instantly—like a live news ticker fed by a real-time data pipeline.
DP-900 Describe an analytics workload on Azure Practice Question
This DP-900 practice question tests your understanding of describe an analytics workload on azure. 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.
A company wants to build a real-time analytics dashboard for IoT sensor data. Which combination of Azure services should they use?
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 and Power BI
Azure Stream Analytics is a real-time event processing engine that can ingest IoT sensor data from sources like Azure Event Hubs, apply SQL-based queries to detect patterns or anomalies, and output results directly to Power BI for live dashboard visualization. This combination provides end-to-end streaming analytics with sub-second latency, which is essential for real-time dashboards.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 HDInsight and Azure Databricks
Why it's wrong here
Both are for batch or near-real-time, not sub-second streaming.
✗
Azure Logic Apps and Azure SQL Database
Why it's wrong here
Logic Apps is for workflows, not high-throughput streaming analytics.
✗
Azure Data Factory and Azure Analysis Services
Why it's wrong here
Data Factory is batch-oriented; Analysis Services is for offline models.
✓
Azure Stream Analytics and Power BI
Why this is correct
Stream Analytics provides real-time processing, Power BI displays live dashboards.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse batch processing services (like Azure Data Factory or HDInsight) with real-time streaming services, or assume that any database (like Azure SQL) can handle high-velocity streaming data, but only Stream Analytics provides the necessary event-time processing and low-latency output for live dashboards.
Detailed technical explanation
How to think about this question
Under the hood, Azure Stream Analytics uses a temporal windowing mechanism (e.g., tumbling, hopping, or sliding windows) to aggregate IoT sensor data in near real-time, leveraging a SQL-like query language that compiles to a continuous execution plan. Power BI receives the output via the streaming dataset API, which updates visuals automatically without requiring manual refresh, enabling sub-second dashboard updates. A real-world scenario is monitoring thousands of temperature sensors in a factory; Stream Analytics can detect when a reading exceeds a threshold and push an alert to Power BI within seconds, while batch solutions would introduce minutes of delay.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Stream Analytics and Power BI — Azure Stream Analytics is a real-time event processing engine that can ingest IoT sensor data from sources like Azure Event Hubs, apply SQL-based queries to detect patterns or anomalies, and output results directly to Power BI for live dashboard visualization. This combination provides end-to-end streaming analytics with sub-second latency, which is essential for real-time dashboards.
What should I do if I get this DP-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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