Earlier quoted context omitted.
But couldn't R have applications in business (industry)? A businessperson once asked me about R after he read a non-technical article about it in a major newspaper. This person has never been in academia. Why was he curious? What could he possibly see in R? I see R as a "disruptor" to the market that SPSS has had under lock and key for as long as I can remember. Perhaps statistics has utility outside of academics? Ma…
Certainly it does. Perhaps I shouldn't have emphasized academics so much. Anyone who does in-depth statistical analysis can use R. It is equivalent to SPSS, SAS, and matlab in its applicability, plus its free. People involved in 'big data' and serious analytics in business are already using R a lot of the time. The other group of people in business who use the closed source applications above, however, aren't as tech…
I use R to prototype machine learning techniques on a small set of data, or visualize some summary statistics. But if I want to run K-Means Clustering or Support Vector Machine algorithms on 1,000,000,000 rows of data, I've found that running R on Hadoop is tricky. There are some libraries out there ( for example, RHadoop https://github.com/RevolutionAnalytics/RHadoop/wiki/rmr ) but they require writing your algorithm in such a manner that algorithms must be adapted to run within map() and reduce() functions. My understanding is that the built-in functions that make R so useful will often not adapt well to a mapreduce algorithm.
From what I've seen, once an algorithm is prototyped in something like R/Matlab, if the data size warrants it, it's best to re-write the algorithm in Java MapReduce or use Apache Mahout.