HDInsight Essentials, 2nd Edition

Learn how to build and deploy a modern big data architecture to empower your business

About This Book

• Learn how to quickly provision a Hadoop cluster using Windows Azure Cloud Services
• Build an end-to-end application for a big data problem using open source software
• Discover more about modern data architecture with this guide, to help you understand the transition from legacy relational Enterprise Data Warehouse

Who This Book Is For

If you want to discover one of the latest tools designed to produce stunning Big Data insights, this book features everything you need to get to grips with your data. Whether you are a data architect, developer, or a business strategist, HDInsight adds value in everything from development, administration, and reporting.

In Detail

Traditional relational databases are today ineffective with dealing with the challenges presented by Big Data. A Hadoop-based architecture offers a radical solution, as it is designed specifically to handle huge sets of unstructured data.

This book takes you through the journey of building a modern data lake architecture using HDInsight, a Hadoop-based service that allows you to successfully manage high volume and velocity data in the Microsoft Azure Cloud. Featuring a wealth of practical examples, you’ll find tips and techniques to provision your own HDInsight cluster to ingest, organize, transform, and analyze data.

While guided through HDInsight, you’ll explore the wider Hadoop ecosystem with plenty of working examples on Hadoop technologies including Hive, Pig, MapReduce, HBase, Storm, and analytics solutions including using Excel PowerQuery, PowerMap, and PowerBI.

Table of Contents

Chapter 1: Hadoop and HDInsight in a Heartbeat
Chapter 2: Enterprise Data Lake using HDInsight
Chapter 3: HDInsight Service on Azure
Chapter 4: Administering Your HDInsight Cluster
Chapter 5: Ingest and Organize Data Lake
Chapter 6: Transform Data in the Data Lake
Chapter 7: Analyze and Report from Data Lake
Chapter 8: HDInsight 3.1 New Features
Chapter 9: Strategy for a Successful Data Lake Implementation