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Stream Analytics with Microsoft Azure

You're reading from Stream Analytics with Microsoft Azure

Product type Book

Published in Dec 2017

Publisher Packt

ISBN-13 9781788395908

Pages 322 pages

Edition 1st Edition

Languages

Concepts

Cloud Computing

Authors (2):

Ryan Murphy

Manpreet Singh

View More author details

Table of Contents (18) Chapters

Title Page

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Introducing Stream Processing and Real-Time Insights

2. Introducing Azure Stream Analytics and Key Advantages

3. Designing Real-Time Streaming Pipelines

4. Developing Real-Time Event Processing with Azure Streaming

5. Building Using Stream Analytics Query Language

6. How to achieve Seamless Scalability with Automation

7. Integration of Microsoft Business Intelligence and Big Data

8. Designing and Managing Stream Analytics Jobs

9. Optimizing Intelligence in Azure Streaming

10. Understanding Stream Analytics Job Monitoring

11. Use Cases for Real-World Data Streaming Architectures

Comparison between Azure Stream Analytics and Azure HDInsight Storm

Microsoft announced the availability of a managed real-time data stream engine- Azure Stream Analytics in late 2014, then within a few months, also declared the offering of an interactive open source big data framework—Apache Storm with Azure Hadoop clusters as HDInsight Storm. As an open source tool, Storm with HDInsight has got the capability of integrating with programming languages like Java and Python along with support in Visual Studio IDE using .NET-based APIs for development on Storm applications, Storm HBase, Storm Event Hub, Storm with Document DB/Azure SQL DB reader, and writer sample demos. Both real-time stream processing solutions are offered as managed Platform as a Service (Paas) models, where users will be charged per unit of clusters and the number of running Storm cluster hours in HDInsight; whereas Stream Analytics charging is based on the provisioned number of Streaming Units and the amount of data processed...

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Authors (2)

Ryan Murphy

Ryan Murphy, one of the key Co-authors of Stream Analytics with Microsoft Azure is a Solution Architect living in Saint Louis, Missouri. He has been building and innovating with data for nearly twenty years, including extensive work in the gaming and agriculture industries. Currently, Ryan is helping some of the worlds largest organizations modernize their business with data solutions powered by the Microsoft Azure cloud.

See other products by Ryan Murphy

Manpreet Singh

Manpreet Singh is a consultant and author with extensive expertise in architecture, design, and implementation of business intelligence and Big Data analytics solutions. He is passionate about enabling businesses to derive valuable insights from their data. Manpreet has been working on Microsoft technologies for more than 10 years, with a strong focus on Microsoft Business Intelligence Stack, SharePoint BI, and Microsofts Big Data Analytics Platforms (Analytics Platform System and HDInsight). He also specializes in Mobile Business Intelligence solution development and has helped businesses deliver a consolidated view of their data to their mobile workforces. Manpreet has coauthored books and technical articles on Microsoft technologies, focusing on the development of data analytics and visualization solutions with the Microsoft BI Stack and SharePoint. He holds a degree in computer science and engineering from Punjab University, India.

See other products by Manpreet Singh

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