Building Streaming Data Pipelines in Microsoft Azure

Do you need to process live data streams from sensors, custom apps, IoT devices, and logs? Do you need to immediately respond to anomalies and patterns in live data streams? Are you familiar with T-SQL? If so, Azure Stream Analytics is for you.
Course info
Rating
(17)
Level
Intermediate
Updated
Oct 23, 2019
Duration
1h 57m
Table of contents
Description
Course info
Rating
(17)
Level
Intermediate
Updated
Oct 23, 2019
Duration
1h 57m
Description

Processing live data streams in real time can be challenging and expensive. In this course, Building Streaming Data Pipelines in Microsoft Azure, you will gain the ability to effectively use Azure Stream Analytics for your live data processing needs. First, you will learn to configure stream and reference inputs for the service. Next, you will discover how to process your data using the Stream Analytics Query Language. Finally, you will explore how to visualize Azure Stream Analytics output with Microsoft Power BI. When you are finished with this course, you will have the skills and knowledge of Azure Stream Analytics needed to turn your live stream data into meaningful, actionable information.

About the author
About the author

Reza, is a Microsoft Azure and Amazon AWS architect, developer and trainer. He continues helping his clients with cloud-native solutions while sharing his expertise with other developers through training and mentoring.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi everyone. My name is Reza Salehi, and welcome to my course, Building Streaming Data Pipelines in Microsoft Azure. I am a cloud consultant and trainer. There are many sources providing live data streams from the stock market and banking applications to industrial sensors and connected IoT devices. This live data needs to get processed and _____ active often in real time. In this course, we are going to use Azure Stream Analytics to process live data streams. Some of the major topics that we will cover include understanding windowing functions, configuring the stream and reference inputs, the Stream Analytics query language, and finally, integrating the output with Power BI. By the end of this course, you will know Azure Stream Analytics well enough to build your own live data processing pipeline. Before beginning the course, you should be familiar with Azure Portal and T-SQL. I hope you'll join me on this journey to learn Azure Stream Analytics with the Building Streaming Data Pipelines in Microsoft Azure course, at Pluralsight.