Phil Simon, author of Too Big to Ignore: The Business Case for Big Data, continues his discussion on the myths of collecting and analyzing data. For further reading on the subject, read part one of this two-part series.
Myth: Big Data results in certainty
A well-trodden business aphorism is, “I have all of the data I can handle. I just need more information.” In Too Big to Ignore: The Business Case for Big Data, I write about the difficulty of being truly certain about business decisions of any import. It’s virtually impossible to be completely sure about a merger, product launch, new venture, or even an individual employee hire.
But isn’t Big Data supposed to help us with uncertainty? Yes, but don’t confuse reducing uncertainty with eliminating it. That day isn’t here yet, and I suspect that it won’t arrive anytime soon.
Analyzing petabytes of unstructured data may well help companies better understand customer sentiment. However, don’t make the mistake of assuming that Big Data eliminates all variability. The vicissitudes of life and business will still throw a wrench into the best of plans.
Myth: Big Data is a fad
Arguably, the current face of Big Data is Nate Silver. The blogger and statistician famously predicted that Barrack Obama was a 90-percent favorite to win the 2012 U.S. Presidential election, despite the fact that polls put Obama in a virtual dead heat with Mitt Romney. Silver’s model was remarkably accurate, and now everyone is asking for his take on everything.
To be sure, the terms Big Data and data science may vanish into the ether over the next few years. We do like our buzzwords and jargon. Foolish is the professional, however, who believes that data is a fad. I’m sure of very few things, but I know that in 2013 we will collectively generate and consume more data than we did in 2012.
It’s high time that organizations get on board the Big Data train. Laggards who refuse to recognize its importance may not be around when the light bulb finally goes off.