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The Real Lesson for Data Science That is Demonstrated by Palantir's Struggles Buzzfeed recently published a long article on the struggles of the secretive data science company, Palantir. Over the last 13 months, at least three top-tier corporate clients have walked away, including Coca-Cola, American Express, and Nasdaq, according to internal documents. Palantir mines data to help companies make m
There is a lot of noise around the “R versus Contender X” for Data Science. I think the two main competitors right now that I hear about are Python and Julia. I’m not going to weigh into the debates because I go by the motto: “Why not just use something that works?” R offers a lot of benefits if you are interested in statistical or predictive modeling. It is basically unrivaled in terms of the bre
Code is a useful representation of a data analysis for the purposes of transparency and opennness. But code alone is often insufficient for evaluating the quality of a data analysis and for determining why certain outputs differ from what was expected. Is there a better way to represent a data analysis that helps to resolve some of these questions?
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