Today, massive amounts of real-time data are generated by connected applications, Internet of Things (IoT) devices and sensors, and various other sources. The proliferation of these streaming data sources has made the ability to consume and make informed decisions from these data in near-real-time an operational necessity for many organizations.

To provide a few examples, online stores analyze real-time clickstream data to provide product recommendations to consumers as they browse the website. Manufacturing facilities utilize telemetry data from IoT sensors to remotely monitor high-value assets. And credit card transactions from point-of-sale systems are scrutinized in real-time to detect and prevent potentially fraudulent activities.

Azure Stream Analytics seamlessly integrates your real-time application architecture with a streaming analytics engine to transform streaming data into actionable insights. Using Azure Stream Analytics enables powerful, real-time analytics on your data no matter what the volume.

In this module, you will learn how real-time analytics of streaming data works, in principle. You will also discover how you can use Azure Stream Analytics to integrate streaming data into your real-time analytics workflows.

Learning objectives

In this module, you will:

  • Understand data streams
  • Understand event processing
  • Learn about processing events with Azure Stream Analytics