Azure Stream Analytics is a cloud-based service for ingesting high-velocity data streaming from devices, sensors, applications, Web sites, and other data sources and analyzing that data in real time. It supports a SQL-like query language that works over dynamic data streams and makes analyzing constantly changing data no more difficult than performing queries on static data stored in traditional databases. With Azure Stream Analytics, you can set up jobs that analyze incoming data for anomalies or information of interest and record the results, present notifications on dashboards, or even fire off alerts to mobile devices. And all of it can be done at low cost and with a minimum of effort.
Scenarios for the application of real-time data analytics are legion and include fraud detection, identity-theft protection, optimizing the allocation of resources (think of an Uber-like transportation service that sends drivers to areas of increasing demand before that demand peaks), click-stream analysis on Web sites, shopping suggestions on retail-sales sites, and countless others. Having the ability to process data as it comes in rather than waiting until after it has been aggregated offers a competitive advantage to businesses that are agile enough to make adjustments on the fly.
In this lab, you'll create an Azure Stream Analytics job and use it to analyze data streaming in from simulated Internet of Things (IoT) devices. And you will see how simple it is to monitor real-time data streams for information of significance to your research or business.
In this hands-on lab, you will learn how to:
Click here to download a zip file containing the resources used in this lab. Copy the contents of the zip file into a folder on your hard disk.
This hands-on lab includes the following exercises:
Estimated time to complete this lab: 60 minutes.