Book Image

Practical Big Data Analytics

By : Nataraj Dasgupta
Book Image

Practical Big Data Analytics

By: Nataraj Dasgupta

Overview of this book

Big Data analytics relates to the strategies used by organizations to collect, organize, and analyze large amounts of data to uncover valuable business insights that cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization’s data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages, and BI tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology and the practical reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB, and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using the different tools and methods articulated in this book.
Table of Contents (16 chapters)
Title Page
Packt Upsell
Contributors
Preface

Summary


Big data is undoubtedly a vast subject that can seem overly complex at first sight. Practice makes perfect, and so it is with the study of big data--the more you get involved, the more familiar the topics and verbiage gets, and the more comfortable the subject becomes.

A keen study of the various dimensions of the topic of big data analytics will help you develop an intuitive sense of the subject. This book aims to provide a holistic overview of the topic and will cover a broad range of areas such as Hadoop, Spark, NoSQL databases as well as topics that are based on hardware design and cloud infrastructures. In the next chapter, we will introduce the concept of Big Data Mining and discuss about the technical elements as well as the selection criteria for Big Data technologies.