With the rise of predictive analytics, statistical computing software like SAS, R and SPSS are playing a vital role in driving fast analysis of large data sets with complex algorithms.
Of those three statistical languages, R is the only one that is open source. SAS is the largest privately held software company in the world, and SPSS is now shepherded by IBM.
Revolution Analytics provides an enterprise distribution of R. The company is looking to battle both SAS and SPSS on price, performance on distributed and massively parallel computing, and adoption in the cloud, according to Davis Smith, Revolution’s vice president of marketing and community.
Smith admitted it is an uphill battle. SAS, a company that was founded 40 years ago, is used by most Fortune 500 companies. But Smith said because R is open source and costs nothing to download, it’s widely used in academic settings and most new graduates with statistics and analytics degrees have used R.
Revolution Analytics has also focused on connecting R with other companies, including IBM and Jaspersoft, to provide business intelligence platforms, connect to Hadoop, NoSQL databases and data in the cloud. The resulting ecosystem, Smith said, is as robust as any all-in-one data stack, he said.
In this interview with Data Informed Staff Writer Ian B. Murphy, Smith discusses how R was started and why it continues as one of the longest open source projects, the additional features Revolution Analytics’ distribution has compared to stock R, and how it’s battling with SAS to become the most used statistical computing language. (Podcast running time: 21:41.)
Email Staff Writer Ian B. Murphy at firstname.lastname@example.org. Check out other Analytics podcasts from Data Informed.
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