If you work in the analytics world, you’ve probably either read or at least heard of the seminal book "Big Data: A Revolution That Will Transform How We Live, Work and Think," published earlier this year. Authors Viktor Mayer-Schonberger and Kenneth Cukier’s provocative point of departure is that the new data norm of N=all and a tolerance for simple correlation over causation is changing the analytics landscape, obviating the need for much of traditional statistical analyses.

Not so fast has been the response of many. Harvard professor and big data advocate Gary King argues that it’s as much about analytical methods and research design as the data.  Algorithms and methodology are just as important as data quantity. “The trick is to make yourself vulnerable to being proven wrong as many times as possible.”

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