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.
What You Will Learn
- Explore core features of Hadoop, including the HDFS2 and YARN, the new resource manager for Hadoop
- Build your HDInsight cluster in minutes and learn how to administer it using Azure PowerShell
- Discover what's new in Hadoop 2.X and the reference architecture for a modern data lake based on Hadoop
- Find out more about a data lake vision and its core capabilities
- Ingest and organize your data into HDInsight
- Utilize open source software to transform data including Hive, Pig, and MapReduce, and make it available for decision makers
- Get to grips with architectural considerations for scalability, maintainability, and security
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.
