DP-900 Describe an analytics workload on Azure Practice Question
A logistics company uses IoT sensors on delivery trucks to transmit GPS location, speed, and engine diagnostics every 10 seconds. The data is ingested into Azure Event Hubs. The company needs to analyze the data in real time to identify speeding trucks and send alerts. The analysis requires joining the live sensor data with a reference table of truck details (e.g., driver name, route number) stored in Azure SQL Database. Which Azure service should they use for the real-time processing?
⚠ Common exam trap
It's easy for candidates to confuse batch-oriented services like Azure Synapse Analytics or Azure Data Factory with real-time processing, or they overcomplicate the solution by choosing Azure Databricks when a simpler, purpose-built service like Stream Analytics is sufficient for the join-and-alert pattern.
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 a real-time event processing engine designed to handle streaming data from sources like Azure Event Hubs. It can perform temporal joins between the live IoT sensor stream and a static reference table (e.g., truck details from Azure SQL Database) to enrich the data and trigger alerts when speeding is detected, all with sub-second latency.
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 built specifically for real-time stream processing over sources such as Azure Event Hubs and IoT Hub. It continuously consumes telemetry events and executes a declarative SQL-based query engine that can apply tumbling, hopping, or sliding windows to detect patterns like speeding while joining live data with reference data from Azure SQL Database. Its low-latency, in-memory processing and native outputs to alerts, Azure Functions, or Power BI make it the natural fit for this scenario.
- ✗
Azure Synapse Analytics dedicated SQL pool
Why it's wrong here
Azure Synapse Analytics dedicated SQL pool is a massively parallel processing (MPP) data warehouse for high-concurrency, relational analytics over stored data, not for low-latency event processing. While you can land Event Hubs data into a SQL pool using a pipeline or PolyBase, that batch-oriented load introduces significant delay and does not provide continuous stream queries or real-time alerting. The service is optimized for T-SQL queries and star-schema workloads, not for evaluating speeding events as they occur.
- ✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is a cloud-scale ETL and data orchestration service that moves and transforms data on schedules, tumbling windows, or event-driven triggers such as blob storage events, but it is fundamentally a batch and pipeline orchestrator. It lacks a built-in query engine for stateful, time-windowed stream processing, so it cannot evaluate each IoT telemetry event in sub-second latency to issue a speeding alert. Using Data Factory here would require an external engine to do the analysis, and the orchestration overhead would still miss the real-time requirement.
- ✗
Azure Databricks
Why it's wrong here
Azure Databricks is not the optimal choice for the immediate, low-latency real-time stream processing and alerting required here, as its typical micro-batch processing introduces higher latency compared to dedicated stream analytics solutions. However, it is a powerful unified analytics platform, excellent for large-scale data engineering, complex transformations, and machine learning workloads. It would be suitable for deeper, historical analysis of the truck data, building predictive models, or complex ETL pipelines, where immediate, sub-second alerting is not the primary concern.
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Data Roles and Core Concepts
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
Azure SQL Database
Azure SQL Database is a fully managed relational database-as-a-service (DBaaS) in Microsoft Azure, based on the SQL Server engine, that handles scaling, backups, patching, and high availability automatically.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-900 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-900 exam.