I met up with my old analytics friend a few weeks back. Throughout the ‘90s, we shared statistical war stories from our respective SAS consulting customers. Around 2000, I made the software leap to first S+ and then R, while he remained loyal to SAS. Since that time, we’ve stayed close, but there’s generally a bit of a SAS-R edge to our statistical discussions.
My friend and I probably see each other’s statistical product choice as a series of stereotypes. For him, R’s open source development model presents serious quality risks in contrast to the tried-and-true proprietary SAS QA methods. Compared to SAS’s serious enterprise business focus that includes data integration and BI, he argues that R’s simply for academics and researchers. And, of course, R’s in-memory processing limitation consigns it to toy data only.
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