The rise of R as the language of analytics

November 22, 2013

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

It's no coincidence that while the usage of the R language is skyrocketing (as shown in the recent Rexer Analytics and KDNuggets polls), the growth in data scientist jobs is also skyrocketing. R is the lingua franca of data science, and as the pervasive statistical software in the academic sector, there's a steady-stream of newly-minted graduates trained in R, data science, and often other open-source technologies including Hadoop.

A couple of weeks ago, I sat down with DataInformed's Michael Goldberg to talk about the rise of R as the analytics programming language for business. The interview covered a wide range of topics, including:

  • How the Big Data movement has led companies to set up data science teams to extract value from all the data they have collected and stored;
  • That because R is the lingua franca of data science, businesses are rapidly adopting R to support these data science programs 
  • How new data platforms like Hadoop, which are often though of as data storage platforms, can also be powerful data science platforms with the in-Hadoop and in-Database capabilities of Revolution R Enterprise.
  • Ways to solve the "last mile problem" of delivering the results of predictive models to those in the company that will make decisions using those prediction; and
  • The importance of the open source community for users of analytics software

You can listen to the full 20-minute interview at the link below.

Data Informed: The Rise of R as an Analytics Programming Language for Business

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