ExpertMedium1 markMultiple Choice
AZ-305 · Question 21 · Domain 2.2: Data Integration
You are designing an IoT architecture for a manufacturing plant. Thousands of sensors will send temperature and pressure telemetry every second.
You need to ingest this massive stream of telemetry data, calculate the average temperature over a 5-minute tumbling window, and trigger an alert if the average exceeds a threshold. The raw data must also be saved to Azure Data Lake Storage for historical analysis.
Which TWO Azure services should you combine to achieve this? (Select TWO)
You are designing an IoT architecture for a manufacturing plant. Thousands of sensors will send temperature and pressure telemetry every second.
You need to ingest this massive stream of telemetry data, calculate the average temperature over a 5-minute tumbling window, and trigger an alert if the average exceeds a threshold. The raw data must also be saved to Azure Data Lake Storage for historical analysis.
Which TWO Azure services should you combine to achieve this? (Select TWO)
Answer options:
A.
Azure IoT Hub
B.
Azure Service Bus
C.
Azure Stream Analytics
D.
Azure Data Factory
E.
Azure Event Grid
How to approach this question
Identify the ingestion service for IoT devices and the processing service for real-time windowing.
Full Answer
Azure IoT Hub, Azure Stream Analytics
For IoT telemetry ingestion at scale, Azure IoT Hub (or Event Hubs) is the correct entry point. To process this data in real-time, calculate averages over time windows (tumbling, hopping, sliding), and route outputs to multiple destinations (alerts and Data Lake), Azure Stream Analytics is the purpose-built service. Data Factory is for batch, and Service Bus/Event Grid are for discrete messaging, not stream processing.
Common mistakes
Selecting Data Factory for processing. ADF is batch-oriented and cannot do real-time tumbling window calculations.
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