In my last post, we explored how audience data sources from inside and outside of the media organization can be “unified and utilized” for game-changing applications such as demand forecasting for Opening Weekend Box Office (OWBO) using big data analytics.
Our results showed that IBM achieved high
In today’s world, many can compare their big data landscape to a vast wilderness. We know it exists and it is growing in size, volume and complexity – but do we know what is really growing and taking roots. Are there valuable resources that, if mined, could create new growth and opportunities? Or
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
The need to innovate and stay ahead of customer demands is even more imperative today. IDC estimates that “in 2012 the digital universe will grow to 2.7 zettabytes.” As customers and the market as a whole generate data, companies are compelled to capture and analyze an ever-greater percentage of