There is a backlash growing against the term "Big Data." Some of the negativity is just because of hype; people are attaching the name to their company for any reason, absurd reasons, and/or no reason at all.

I recently saw a pitch by a new venture that "creates Big Data for your business." Literally, they will create some for you if you don't already have any. It's hardly the most egregious example. We've seen mega-vendors twist their acquisitions into "Big Data" products, even though some of these technologies are 32-bit only, or have data sheets trumpeting claims like "handle up to 10M records." Big Data, indeed.

Another driver of the backlash is the cognitive dissonance that results from being told Big Data is all about huge data volumes or infrastructure that deal with it. Big Data has clearly emerged in the context of volume, but most companies are not Facebook, Zynga or the Large Hadron Collider. They simply do not have trucks filled with data unexpectedly arriving at the loading docks. Technical and data managers who grok the nature of the problem reject Big Data as a term in this context. They may even call it BS.

Yet another reason is disappointment and/or failure, as a result of overinvesting in "the volume problem." I recently spoke with a large bank that jumped on a popular open source product bandwagon, years before everyone else. They spent a fortune to do what they could have done much more easily and cheaply with existing tools. The lead manager admitted their team was more "driven by volume" and the hyped technologies used by exciting companies. They didn't consider that solving a different problem might produce more value for the bank, much more cost-effectively.

Where is Big Data headed? The good news is that rather than being rejected, the phenomenon of Big Data is morphing. It is becoming the art and science of actually using information to make decisions - more than ever before. And it is being driven by the success of companies that actually do that.

The real Big Data is driven by several factors... for one, the rapid creation of data, including voluminous data, from technical systems that interact with lots of people, where all those interactions are a multiple of the number of transactions that may ultimately occur. Another is the significant fall in the costs of storage and compute power, plus the emergence of 64-bit platforms that can use far more memory. But the real, underlying driver is...value.

Companies that have combined data volume with ubiquitous computing power and have actually brought the information together and analyzed it have found more... more customers, more profits and more growth. This is why Big Data is truly a phenomenon. Better approaches can be realized most everywhere. It cuts across industries, sectors, even countries. It is not just about things we have already defined well: volume, velocity, variety, etc. It is about the need to compete, and win, using information. Sometimes it is about figuring out how to get the data to make a better decision, and not just moving forward with gut instinct, in lieu of that.

It will stay big because when you look at what it really takes to make better decisions, there is a lot to it. Structured and unstructured. Internal and external. SQL and NoSQL. Volume, velocity and variety. Big Data is the discovery of how much data is not being used, and then realizing that changing that fact is the real challenge...and the real opportunity.