Get to grips with the exciting features and contents of Big Data Analytics with R and Hadoop using Packt's New Book and eBook!!

December 2013 | Open Source

Packt is pleased to announce the release of Big Data Analytics with R and Hadoop, a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop. This book is available now in print, eBook, Kindle and select library formats. The print book comes in at over 238 pages and is competitively priced at $49.99, whilst the e-book and Kindle versions are available for $25.49

About the Author:
Vignesh Prajapati, from India, is a Big Data enthusiast, a Pingax consultant and a software professional at Enjay. He is an experienced ML Data engineer. He is experienced with Machine learning and Big Data technologies such as R, Hadoop, Mahout, Pig, Hive, and related Hadoop components to analyze datasets to achieve informative insights by data analytics cycles. His professional experience includes working on the development of various Data analytics algorithms for Google Analytics data source, for providing economic value to the products. He also contributes to the R community by developing the RGoogleAnalytics' R library as an open source code Google project and writes articles on Data-driven technologies. Vignesh is not limited to a single domain; he has also worked for developing various interactive apps via various Google APIs, such as Google Analytics API, Realtime API, Google Prediction API, Google Chart API, and Translate API with the Java and PHP platforms. He is highly interested in the development of open source technologies.

Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing.

Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop using various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS.

This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. It is also aimed at those who have experience with Hadoop and want to build some intelligent applications using big data with R packages. It would be helpful if readers also have basic knowledge of R.

The following are the chapters emphasized in this book:

Chapter 1: Getting Ready to Use R and Hadoop
Chapter 2: Writing Hadoop MapReduce Programs
Chapter 3: Integrating R and Hadoop
Chapter 4: Using Hadoop Streaming with R
Chapter 5: Learning Data Analytics with R and Hadoop
Chapter 6: Understanding Big Data Analysis with
Machine Learning
Chapter 7: Importing and Exporting Data from Various DBs

Packt Publishing has also released and is due to publish some other big data analytics books:
Pentaho for Big Data Analytics
Getting Started with Greenplum for Big Data Analytics

All Java books are published by Packt Enterprise. Packt Enterprise is a publishing division of Packt Publishing designed to serve the information needs of IT professionals in the enterprise space. Packt Enterprise also publishes on IBM, Microsoft, Citrix, Oracle, Amazon, Google, and SAP technologies.

Anchoring Text – #Big Data Analytics, #R, #Hadoop


Big Data Analytics with R and Hadoop
Get to grips with the exciting features and content of Big Data Analytics with R and Hadoop using Packt's new book and eBook!

For more information, please visit: Book Page

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