As connected devices become more commonplace, we are moving towards a true IoT world, where every device will be connected to the internet and be able to generate a continuous stream of data. This calls for a new requirement of collecting, storing and analyzing this continuous stream of data. To address this need, Azure provides a dedicated analytics service, aptly named, Azure Stream Analytics.
As explained in the diagram above, Azure Stream Analytics is designed to analyze high volumes of high velocity data from multiple sources (primarily IoT data) in real time.
A stream analytics job is fully managed by the Azure cloud, i.e. users do not need to provision any hardware. It is also fully integrated with other Azure services and very easy to setup with a few clicks. The output of the Azure Stream Analytics job can be sent to a visualization service such as PowerBI or can be stored on another Azure analytics service such as Azure HDInsight or Azure Synapse Analytics for further processing.
Azure Stream Analytics provides a simple SQL-based language called, Stream Analytics Query Language. Azure Stream Analytics provides developers, the ability to extend the query language by defining additional Machine Learning functions.
Azure Stream Analytics can process massive amounts of data on the scale of over a million events per second and deliver the results with ultra-low latency.
Azure Stream Analytics is compliant with leading industry certifications such as HIPAA, ISO27001, FedRAMP etc.
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