Ajay Ohri of Decisionstats.com has recently published ‘R for Business Analytics’ with Springer. The book is now available on Amazon at http://www.amazon.com/R-Business-Analytics-A-Ohri/dp/1461443423
The introduction of the book-
R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness.
This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners.
In an Interview with Analytics India Magazine, Ajay talks about his experience of writing the book and about his take on R and similar statistical software.
AIMAnalytics India Magazine: How did you decide to write a book on R especially for Business Analytics professionals?
AOAjay Ohri: I got involved in R in 2007 when I created my startup in business analytics consulting, since I could not afford my existing tool called Base SAS. After learning it for a couple of years, I found that the existing documentation and literature was aimed more at statisticians than at MBAs like me who wanted to learn R for Business Analytics. So I sent a proposal to Springer Publishing and they accepted and so I wrote the book.
AIM: What did it take to have a book published?
AO: An idea, a good proposal, and 2 years of writing and 6 months of editing. Lots of good luck, and good wishes from my very patient instructors and mentors across the world.
AIM: How is R different from other statistical tools available in market? What are its strengths and weaknesses vis-à-vis SAS and SPSS?
AO: R is fundamentally different from SAS language (which is divided into procedures and data steps) and the menu driven SPSS. It is object oriented, much more flexible, hence powerful, yet confusing to the novice, as there are multiple ways to do anything in R. It is overall a very elegant language for statistics and the strengths of the language are enhanced by nearly 5000 packages developed by leading brains across the universities of the planet.
AO: I use R Commander and Rattle a lot, and I use the dependent packages. I use car for regression, and forecast for time series, and many packages for specific graphs. I have not mastered ggplot though but I do use it sometimes. Overall I am waiting for Hadley Wickham to come up with an updated book to his ecosystem of packages as they are very formidable, completely comprehensive and easy to use in my opinion, so much I can get by the occasional copy and paste code.
AIM: What level of adoption do you see for R as a preferred tool in the industry? Are Indian businesses also keen to adopt R?
AO: I see surprising growth for R in Business, and I have had to turn down offers for consulting and training as I write my next book R for Cloud Computing. Indian businesses are keen to cut costs like businesses globally, but have an added advantage of having a huge pool of young engineers and quantitatively trained people to choose from. So there is more interest in India for R, but is growing thanks to the efforts of companies like SAP, Oracle, Revolution Analytics and R Studio who have invested in R and are making it more popular. The R Project organization is dominated by academia, and this reflects the fact their priorities is making the software better, faster, stabler but the rest of the community has been making efforts to introduce it to industry.
AIM: How did you start your career in analytics and how were you first acquainted with R?
AO: I started my career after MBA in selling cars, which was selling a lot of dreams and managing people telling lies to people to sell cars. So I switched to Business Analytics thanks to GE in 2004, and I had the personal good luck of having Shrikant Dash, ex CEO GE Analytics as my first US client. He was a tough guy and taught me a lot. I came to R only after leaving the cozy world of corporate analytics in 2007.
AIM: Are you working on any other book right now?
AO: I am working on “ R for Cloud Computing” for Springer, besides my usual habit of writing my annual poetry book (which is free) and is tentatively titled “Ulysses in India” . My poetry blog is at http://poemsforkush.com and my technology blog is at http://decisionstats.com and I write there when not writing or pretending to write books.
AIM: What do you suggest to new graduates aspiring to get into analytics space?
AO: Get in early, pick up multiple languages, pick up business domain knowledge, and work hard. Analytics is very lucrative and high growth career. You can read my writings on analytics by just googling my name.
AIM: How do you see Analytics evolving today in the industry as a whole? What are the most important contemporary trends that you see emerging in the Analytics space across the globe?
AO: I don’t know how analytics will evolve, but it will grow bigger and more towards the cloud and bigger data sizes. Big Data /Hadoop, Cloud Computing, Business Analytics and Optimization, Text Mining, are some of the buzz words that are currently in fashion.
Ajay Ohri is the founder of analytics startup Decisionstats.com. He has pursued graduate studies at the University of Tennessee, Knoxville and the Indian Institute of Management, Lucknow. In addition, Ohri has a mechanical engineering degree from the Delhi College of Engineering. He has interviewed more than 100 practitioners in analytics, including leading members from all the analytics software vendors. Ohri has written almost 1300 articles on his blog, besides guest writing for influential analytics communities. He teaches courses in R through online education and has worked as an analytics consultant in India for the past decade.
Ohri was one of the earliest independent analytics consultant in India, and his current research interests include spreading open source analytics, analyzing social media manipulation, simpler interfaces to cloud computing and unorthodox cryptography.