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Big Data Visualization

Big Data Visualization

By : James D. Miller
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Big Data Visualization

Big Data Visualization

2 (1)
By: James D. Miller

Overview of this book

Gain valuable insight into big data analytics with this book. Covering the tools you need to analyse data, together with IBM certified expert James Miller?s insight, this book is the key to data visualization success. ? Learn the tools & techniques to process big data for efficient data visualization ? Packed with insightful real-world use cases ? Addresses the difficulties faced by professionals in the field of big data analytics
Table of Contents (9 chapters)
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About R


We've dabbled a little bit in Chapter 2, Access, Speed, and Storage with Hadoop, with R programming, but in this chapter, we now formally introduce R as the tool to perform our data profiling exercises as well as adding perspectives (establish context) for data to be used in visualizations.

R is a language and environment easy to learn, very flexible in nature, and also very focused on statistical computing thus making it great for manipulating, cleaning, summarizing, producing probability statistics, and so on (as well as actually creating visualizations with your data), so it's a great choice for the exercises required for profiling, establishing context, and identifying additional perspectives.

In addition, here are a few more reasons to use R when profiling your big data:

  • R is used by a large number of academic statisticians, so it's a tool that is not going away.

  • R is pretty much platform independent, what you develop will run almost anywhere.

  • R has awesome help resources--just Google...

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