Why big data doesn't require a big idea

The article discusses how bigger is not better when choosing one's first big data project. Controlled experimentation as a corporate strategy for learning about big data flies in the face of the common misconception that companies should only embrace mature technologies with clear ROI. It is a myth that leveraging big data demands a big idea. Sure, big ideas are fun. Some big ideas really do change the world, thankfully. But when one really digs into how big ideas are operationalized, it becomes clear that good old-fashioned hard work rules the day. This idea is not consistent with all the ill-informed hype but unlike the hype, it happens to be true. One needs to make sure one's project can be done offline and is non-disruptive to existing systems. One should ensure that there is low-hanging fruit for additional insights. One should use a data set that is already stored, but under-instrumented or overly summarized. One should choose a project where initial findings can be arrived at in 4 weeks or less once the data is ready.