The newly emergent “big data” meme has never been defined in any meaningful and definitive way. It’s the most amorphous new buzz-term that I’ve seen for a decade. It’s one of those “eye of the beholder” terms used to liven up a seminar and eventually soak investors.
Let’s start by asking what does big data mean? Lots of data? More data than you can handle? Amorphous data? Out of control data? Useful data for analysis? Useless data? Information overload?
If you read enough about big data, it is all of the above and more. The key is not the data, but the challenge of how to handle the data and what to do with the data itself.
In other words, how can we make this huge pile of data, that we have managed to accumulate, be useful in new and profitable ways? The data pools can come from anywhere via various computing mechanisms such as Facebook posts, NSA logs, mailing lists, customers, etc.
I would argue that most readers of this column are themselves repositories of big data. I just bought a 3 Terabyte drive for backup. I have a lot of data to back up! Big data!