Which three sources can stream input to an Azure Stream Analytics job?

An Azure Stream Analytics job is designed to process and analyze large streams of data in real-time, making it essential to understand the various input sources that can be utilized.

The correct answer identifies three primary sources that can stream data into an Azure Stream Analytics job: IoT Hub, Event Hub, and Blob storage.

IoT Hub is specifically built to handle the millions of IoT devices that can send telemetry data, and integrating it with Stream Analytics allows for real-time analytics on data generated by IoT devices. Event Hub serves as a highly scalable data streaming platform and event ingestion service that can receive and process millions of events per second, making it another critical input source. Blob storage, on the other hand, allows for the storage of large amounts of unstructured data, including files and logs, which can be processed as input to the analytics job. This combination of input sources provides a robust mechanism for collecting data from a variety of platforms and processing it efficiently in real-time.

Other options, such as SQL queries or BI-related components, do not directly serve as streaming inputs for Stream Analytics jobs. While they are important in the analytics process, they do not align with the streaming aggregation capabilities offered by IoT Hub, Event Hub, and Blob storage