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Practical Big Data Analytics

Practical Big Data Analytics

By : Nataraj Dasgupta
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Practical Big Data Analytics

Practical Big Data Analytics

5 (1)
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 (13 chapters)
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Big Data With Hadoop

Hadoop has become the de facto standard in the world of big data, especially over the past three to four years. Hadoop started as a subproject of Apache Nutch in 2006 and introduced two key features related to distributed filesystems and distributed computing, also known as MapReduce, that caught on very rapidly among the open source community. Today, there are thousands of new products that have been developed leveraging the core features of Hadoop, and it has evolved into a vast ecosystem consisting of more than 150 related major products. Arguably, Hadoop was one of the primary catalysts that started the big data and analytics industry.

In this chapter, we will discuss the background and core concepts of Hadoop, the components of the Hadoop platform, and delve deeper into the major products in the Hadoop ecosystem. We will learn about the core concepts...

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