"But while big data promise much to scientists, entrepreneurs and governments, they are doomed to disappoint us if we ignore some very familiar statistical less

"But while big data promise much to scientists, entrepreneurs and governments, they are doomed to disappoint us if we ignore some very familiar statistical lessons. “There are a lot of small data problems that occur in big data,” says Spiegelhalter. “They don’t disappear because you’ve got lots of the stuff. They get worse.”" This should be the main learning point. Humans can be astonishingly bad at dealing with stats and biases which can led to erroneous decisions being made. If you want an example where such decisions by very smart people can have catastrophic consequences, look up the Challenger disaster [1]. I rarely see people stating their assumptions upfront, which doesn't help the problem (I guess it's not cool to admit potential weaknesses). The more people/companies that get into 'big data' (without adequate training) the more false positives we're going to see. [1] http://en.wikipedia.org/wiki/Space_Shuttle_Challenger_disaster http://en.wikipedia.org/wiki/Space_Shuttle_Challenger_disast...