Book Image

Big Data Analytics with R

By : Simon Walkowiak
Book Image

Big Data Analytics with R

By: Simon Walkowiak

Overview of this book

Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.
Table of Contents (16 chapters)
Big Data Analytics with R
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface

Acknowledgement

The inspiration for writing this book came directly from the brilliant work and dedication of many R developers and users, whom I would like to thank first for creating a vibrant and highly-supportive community that nourishes the progress of publicly accessible data analytics and development of R language. However, this book would never be completed if I wasn’t surrounded with love and unconditional support from my partner Ignacio, who always knew how to encourage and motivate me, particularly in moments of my weakness and when I lacked creativity.

I would also like to thank other members of my family, especially my father Peter, who despite not sharing my excitement of data science, always listens patiently to my stories about emerging Big Data technologies and their use cases.

Also, I dedicate this book to my friends and former colleagues from UK Data Service at the University of Essex, where I had an opportunity to work with amazing individuals and experience the best practices in robust data management and processing.

Finally, I highly appreciate the hard work, expertise and feedback offered by many people involved in the creation of this book at Packt Publishing – especially my content development editor Onkar Wani, publishers, and the reviewers, who kindly shared their knowledge with me in order to create a quality and well-received publication.