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Streaming analytics as a concept offers a lot of potential for near real-time data feeds where insights are demanded on arrival or as part of an aggregated window of time. The use case needs to consider that in a stream the query defined doesn’t change but the data does change as it flows through. By comparison in a typical batch workload, the data doesn’t change (relatively speaking in a table loaded daily/weekly), but the query written does change to deliver different outputs as required including different attributes.
Azure Stream Analytics plays into these concepts perfectly whereby the resource offers a series of inputs from Azure IoT Hub and Azure Event Hub, for example. And a series of outputs to Power BI, for example. And the ability to write a query connecting both input(s) and output(s) with a defined output from the query as required for the use case. This query is written in a SQL-like syntax and offers support for user defined functions including the ability for real-time scoring from Azure Machine Learning models.
See MS Learn for more information on this Resource here.
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