Careful: Your big data analytics may be polluted by data scientist bias

Gigaom

Expectations surrounding the future of  big data range from the just huge to absolutely enormous – a reflection perhaps of both its real inherent potential and all the massive hype. Certainly though there is no dispute that companies can reap big benefits from exploring patterns found in the data they already generate and collect. Further, depending on the algorithms used, machine learning can even serve as a real world crystal ball: There are countless examples, but the story about Target’s ability to predict pregnancies by analyzing customer consumption patterns, or how well known mathematician Nate Silver predicted the winner in all 50 states during last November’s presidential election are two poignant examples.

But the fact remains that big data can only ever be as good as the machine learning that is used to provide insight, and even the most sophisticated machine learning techniques aren’t omniscient – the old adage…

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