The popularity of R is no fluke or fad. R has become the common language of data analysis because it was designed – from the ground up – as a practical system for handling the real-world challenges of complex data sets. R-based programs are applied routinely to solve problems in real time trading, finance, risk assessment, forecasting, biotechnology, drug development, social networking and more.” – Revolution Analytics Blog Those who are proficient with R are now the hottest commodity in the job market. The salary scale for R professionals are topping the charts.

1. There is no denial that we are at present living in a golden age of big Data. Understanding the
benefits of analytics, market leaders are now turning to open source programming language R in
order to scale their business.
What is R?
A single letter apparently, but R happens to be the lingua franca for big data analysts. R is a free and
open source statistical tool.
To know more about R, read Introduction to R Analytics tool.
Why R?
 It is easy to do operations on lists and tables of data.
 R has the ability to use high end statistical algorithms and techniques out of the boxwith immense ease.
 R is instrumental in providing analytics on the web.
 It can be embedded in Excel. To understand how it works, read A million ways toconnect R and Excel.
 A plethora of visualizations/plots/charts can be generated using R
 Mature community support is available for newbies in R.
Application of R in Data Analytics
 R helps in analyzing stored data chunk wise. This ultimately leads to parallel analysis, only if the
algorithms allow.
 High performing programming languages like C++ and Java can be integrated. The code chunks that are
outsourced from R can be easily covered up under functions. One such package is rJava. C++ and R make
up the RCPP package.
 A new way of dealing with big data is by using alternative interpreters. One of them is pqR (pretty quick
R).
Source: R-Bloggers

2. “The popularity of R is no fluke or fad. R has become the common language of data analysis
because it was designed – from the ground up – as a practical system for handling the real-world
challenges of complex data sets. R-based programs are applied routinely to solve problems in real-
time trading, finance, risk assessment, forecasting, biotechnology, drug development, social
networking and more.” – Revolution Analytics Blog
Those who are proficient with R are now the hottest commodity in the job market. The salary scale for
R professionals are topping the charts.
Register for our Big Data Analytics Course using R and Hadoop, and master this skill set in a short time
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