The emerging challenge for businesses as they manage their big data trends information is determining each trend's "shelf life." For instance, if long-term climate trend is actionable in project planning today, at what point do you revisit the trends analysis to verify that the projects you have forecasted for your pipeline are still worthy?
The job of classifying trend "life cycles" in batch reports was considerably easier from what it is shaping up to be today with big data analytics. Find out more in TechRepublic article on "What today's big data trend analytics do -- and don't -- tell us at: vhttp://tek.io/1w8owNU
it might be easy to predict that certain areas of the world will be exposed to more natural disasters because of global warming, but what if an unexpected climate shift occurs that no one imagined? Or, it might seem straightforward to predict from projections of today's data trends that childhood obesity will create more stress on the healthcare system, but what if new treatments are developed, and this problem substantially diminishes?