R is the name of a popular programming language that has become the tool of choice for data scientists and statisticians around the world. Companies are using analytics to predict things like pricing of their products, how much to spend on ads, whether a drug will turn out to be successful or not etc. and R is helping them analyse historical data to make these predictions.
The business analytics field has been dominated by paid tools such as SAS, Statistica and SPSS (IBM). Even though some of these tools can be very expensive (with software licenses running into millions of dollars), the value coming out of their application is far more and hence companies did not mind spending so much.
R has been a game changer in the analytics industry
R has been developed from S, another programming language created by the Bell labs. While S turned into S-plus, a commercial product, R continued to evolve as a free product. R was initially developed by a bunch of dedicated practitioners. Over time, the core team expanded and thousands of people from around the globe have contributed to making R the way it is now.
R is not the first open-source analytics tool. There were many others before it, Weka being the most notable. Most of the earlier open-source tools struggled with scalability. While they could handle small data sets admirably, they faltered when it came to mid-size or large data sets.
While R is still not the best product to handle massive amounts of data, it has managed to evolve into a remarkably versatile and fast tool when handling moderate amounts of data. And when combined with other open source technologies like Map reduce and Hadoop, R has turned into a “Big data” analytics tool.
So, is R really becoming popular?
R is now considered to be not just the most popular open-source analytic tool in the world but the most popular analytic tool in the world. Estimates about number of users range from 250000 to over 2 million.
If you look at online popularity, R is the hands-down winner. It has more blogs, discussion groups and email lists than any other tool including SAS. Kdnuggets, a popular website on data mining, conducts annual surveys on popularity of various analytic tools and R was again the top choice in most of the surveys.
Business adoption of R
R is surely the tool of choice for most data scientist and analysts. But what about corporate adoption?
Businesses, especially large ones, are generally hesitant to use open-source tools and technologies for a business process that is as critical as data analysis. However, R has slowly won over the hearts of many large corporates.
Companies like Google, Facebook, Genpact, Accenture, MuSigma and many others are increasingly adopting the R platform.
What about job prospects?
R offers bright job prospects for any data scientist – novice or experienced.
Indian companies are increasingly looking at R as a low-cost or no-cost alternative to much more expensive platforms such as the ones offered by SAS or IBM. Companies like Genpact, Accenture and Wipro are encouraging their staff to build expertise on R and associated technologies.
At the same time, organizations expect many of the new hires to already be equipped with knowledge of R. They want them to be familiar with the R tool and how to use it for data analysis.
There is a definite shortage of trained resources in India who can do analytics with R. The few who do have the right skills find themselves in great demand as organizations look to ramp up their R capabilities.