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
(23)
Level
Intermediate
Updated
Jun 30, 2020
Duration
3h 2m
Table of contents
Course Overview
Azure Stream Analytics Overview
Configure Azure Stream Analytics with Event Hub and Blob Storage Inputs
Query Data Using Azure Stream Analytics
Implement Azure Stream Analytics Data Visualization with PowerBI
Anomaly Detection in Azure Stream Analytics
Analyzing Stream Data Using Azure Data Explorer
Description
Course info
Rating
(23)
Level
Intermediate
Updated
Jun 30, 2020
Duration
3h 2m
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
[Autogenerated] Hi, everyone. My name is Resource Ali. He and welcome to my course building is streaming data pipelines in Microsoft measure, I am a Cloud Council tent and trainer. There are many sources providing live data streams from stock market on banking applications to industrial sensors on connected I ot devices. This life data needs to get processed and acted open in real time. In this course, we are going to use as your stream analytics to process life data streams. Some of the major topics that we will cover include understanding windowing functions, configuring extreme on reference, imports the Stream analytics quarry language and finally integrating the output with power bi I. By the end of this course, you'll know Azure Stream analytics well enough to build your own life data processing pipeline before beginning the course. You should be familiar with the Azure portal anti sequel. I hope you'll join me on this journey to learn as your stream analytics with the building streaming data pipelines in Microsoft Azure course at parole site