Book Image

Stream Analytics with Microsoft Azure

By : Krishnaswamy Venkataraman, Anindita Basak, Ryan Murphy, Manpreet Singh
Book Image

Stream Analytics with Microsoft Azure

By: Krishnaswamy Venkataraman, Anindita Basak, Ryan Murphy, Manpreet 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 (18 chapters)
Title Page
About the Authors
About the Reviewers
Customer Feedback

Chapter 1. Introducing Stream Processing and Real-Time Insights

The popularity of stream data platforms is increasing significantly in recent times. Due to the requirement of real-time access to information. Enterprises are transitioning parts of their data infrastructure to a streaming paradigm due to changing business needs. The streaming model presents a significant shift by moving from point queries against stationary data to a standing temporal query that consumes moving data. Fundamentally, we enable insight on the data before it is stored in the analytics repository. This introduces a new paradigm in thinking. Before going deep into stream processing, we have to cover a couple of key basic concepts related to events and stream. In this chapter, we'll explore the basics of the following points:

  • Publish/Subscribe (Pub/Sub)
  • Stream processing
  • Real-Time Insights

The core theme of this book is the Azure Streaming Service. Before diving deeper into Azure Streaming Service, we should take a moment to consider why we need stream processing, or Real-Time Insights, and why it is a tool worth adding to your repertoire.