Will this be the year of the “big data hybrid”? What will become of cross-scale architectures and next best action? Will governance finally take center stage? And will data scientists still be sexy? James Kobielus looks at all this and more in his predictions for 2013.
What's sexy about data science? It has been dubbed the "sexiest occupation" of the 21st century, but you don't see hordes of autograph-seekers and paparazzi flitting around many data scientists. James Kobielus looks at why data science is hot.
Closing the big data talent gap requires tackling the problem from both sides: the people and the technology. Adequately training the data scientists of tomorrow is an obvious and necessary step, but what about the non-data scientists? And what about the technology side? What can we do to make the
In Part I of this series, we looked at the key considerations for an analytic enterprise to stay competitive in today’s world, and in Part II we discussed how those translated into imperatives for a supporting big data platform. In Part III we covered how IBM applied those considerations and
Prediction markets are where data scientists will attain superstar status. It’s no coincidence that the current age of the “superstar” in professional sports began in the 1970s, when the legal constraints that had prevented the most accomplished athletes from seeking top dollar on the open market