The most important unsolved question for Big Data startups is how to make money. I consider myself somewhat of an expert on this, having discovered a thousand ways not to do it over the last two years. Here's my hierarchy showing the stages from raw data to cold, hard cash:
Data
You have a bunch of files containing information you've gathered, way too much for any human to ever read. You know there's a lot of useful stuff in there though, but you can talk until you're blue in the face and the people with the checkbooks will keep them closed. The data itself, no matter how unique, is low value, since it will take somebody else a lot of effort to turn it into something they can use to make money. It's like trying to sell raw mining ore on a street corner; the buyer will have to invest so much time and effort processing it, they'd much prefer to buy a more finished version even if it's a lot more expensive.
To read the full, original article click on this link: PeteSearch: How to turn data into money
