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Stream Analytics with Microsoft Azure

Stream Analytics with Microsoft Azure

By : Murphy, Singh
4.2 (5)
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Stream Analytics with Microsoft Azure

Stream Analytics with Microsoft Azure

4.2 (5)
By: Murphy, Singh

Overview of this book

Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering, Stream Analytics, allows you to process and get actionable insights from different kinds of data in real-time. This book is your guide to understanding the basics of how Azure Stream Analytics works, and building your own analytics solution using its capabilities. You will start with understanding what Stream Analytics is, and why it is a popular choice for getting real-time insights from data. Then, you will be introduced to Azure Stream Analytics, and see how you can use the tools and functions in Azure to develop your own Streaming Analytics. Over the course of the book, you will be given comparative analytic guidance on using Azure Streaming with other Microsoft Data Platform resources such as Big Data Lambda Architecture integration for real time data analysis and differences of scenarios for architecture designing with Azure HDInsight Hadoop clusters with Storm or Stream Analytics. The book also shows you how you can manage, monitor, and scale your solution for optimal performance. By the end of this book, you will be well-versed in using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data.
Table of Contents (12 chapters)
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Preface

In this book, guidance will be provided for data architecture professionals, cloud architects, big data developers, and data scientists who would like to grab an end-to-end understanding of real-time complex streaming architecture. It's a comprehensive guidance on developing real-time event processing with Azure Stream Analysis.

And it's an implementation guidance for interactive data processing in fields such as the Internet of Things (IoT), social media, sensor data processing with BI, integration of streaming analytics with machine learning, and so on.

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