A Taxonomy of Data Science
Hilary Mason[1] and Chris Wiggins[2]:
We’ve variously heard it said that data science requires some command-line fu for data procurement and preprocessing, or that one needs to know some machine learning or stats, or that one should know how to `look at data’. All of these are partially true, so we thought it would be useful to propose one possible taxonomy — we call it the Snice* taxonomy — of what a data scientist does, in roughly chronological order: Obtain, Scrub, Explore, Model, and iNterpret (or, if you like, OSEMN, which rhymes with possum).
The clearest list of what a modern data scientist is supposed to know and do.
Original title and link: A Taxonomy of Data Science (NoSQL databases © myNoSQL)
via: http://www.dataists.com/2010/09/a-taxonomy-of-data-science/
