As data become more abundant (and messy), there is increasing demand for more specialists who could not only separate noise from proverbial "golden nuggets" of information, but also make those "nuggets" useful and actionable:
"Hilary Mason, chief scientist for the URL shortening service bit.ly, says a data scientist must have three key skills. "They can take a data set and model it mathematically and understand the math required to build those models; they can actually do that, which means they have the engineering skills…and finally they are someone who can find insights and tell stories from their data. That means asking the right questions, and that is usually the hardest piece."
It is this ability to turn data into information into action that presents the most challenges. It requires a deep understanding of the business to know the questions to ask. The problem that a lot of companies face is that they don't know what they don't know, as former U.S. Defense Secretary Donald Rumsfeld would say. The job of the data scientist isn't simply to uncover lost nuggets, but discover new ones and more importantly, turn them into actions. Providing ever-larger screeds of information doesn't help anyone."