Why learning R is important in present day context

 If you are wondering what language to learn that is going to give you value for money and time invested, that’s definitely “R”.

While there are so many benefits and reasons why learning ‘R’ is so important today, the most significant among them is that ‘R’ language is here to stay for a long time with its adoption snowballing across industries and solutions. Unlike some others like Pascal and VB6 that have become obsolete, ‘R’ language has a long shelf life, at an estimated 15years or more. So when you learn ‘R’ you are getting value for your investment, besides being able to chalk out a career roadmap that is far-sighted and beneficial for you.

If you are not very sure what R language is all about, let’s decode it. R is a statistical language developed in the mid- 90s, that has today extended tself to analytics, data science, academic research and latently, Big Data. However, it can be used by anybody, even without a formal background in statistics.

Benefits of ‘R’

  • Open source, with underlying code downloaded at no cost or time
  • Easy to use for anyone, programming language not necessary§  Runs on all OS (Operating Systems), on your simple desktop, laptop, Mac, whatever.
  • Does not need internet connection, unless you are inputting any data source from net
  • Can be learned even without being a statistics or mathematics expert, although it does facilitate learning/usage process
  • Data is easy to input, analyse and output
  • Data can be imported from any source – Excel, SAS, SPSS
  • Facilitates analysis and manipulation of data
  • Supports a great graphical display
  • A wide spectrum of R packages available for use
  • Continued development of packages and applications, FREELY available
  • Has found application in enterprise and business anlaytics
  • Inputs Google maps and many other geostatistical functions for processing
  • Extends itself to a Big Data environment
  • Ability to be paired / integrated with other software or technolgy environments (SAS, Hadoop, more)
  • Ability to call R from SAS

Most importantly, THE platform of choice for data scientists, analysts , statisticians, IT professionals, researchers and even geospatial professionals

Now if all this has not convinced you that learning R is important today, read on.

Why do you need R?

Whether you are a student or professional in IT (developing, database, software administration, etc), statistics, social science, sport science, healthcare, data science, research (in any field), Geology or GIS, R is a simple software that extends across all of these domains and more. With its easy learning curve, you can gain mastery over this terrific language. You can make contributions that simplify your tasks and add to your job portfolio, develop applications on your own, and publish the same across the ‘R’ community.  You do not need permissions for any of these. Unlike other proprietary or even open source languages, once you download R, it becomes ‘your baby’. You can develop and work as you move along your career path.

Check out our blogs that give you a Rundown on Big Data technologies (includes R) and How to learn R for free.

Favouriting R as the preferred language for most jobs

I am also sharing my personal reasons for favouriting R, in case this helps you clinch your decision.

R is open source software, which means no annual licence fee payable (wow!), easy and fast to download(while you multitask), free access to plenty of learning tutorials on net and a huge developer community (I share my morning tea with the R-Bloggers – kicking off each day learning something new). What’s more, it’s a great data processor, can be used in my papers (yes, I have used in EIA as well as epidemiology!) , enhances presentations I make on any topic with its coloured graphical displays and recently, its ability to input Google map that has me over the moon! . With its analytics and Geostatistical capabilities, integration with Hadoop and SAS, this is the most prolific open source software, and you must learn this. Okay, so I may be partial to R, but surely not without reason!


Simple graphics – Part of a contaminant analysis task executed using R