"Big data" entered our language before anyone knew what it meant. So then we spent a lot of time discussing it: "Is it really about the ‘bigness’?”, “Isn’t it about non-relational data?”, “No wait, it’s about the the need for speed." This got boiled down to the three Vs (volume, variety, velocity), but then “big data” just meant three things, which didn’t clarify much at all.
So we, the tech community, are developing new vocabulary and distinctions, and in 2013, no one is going to say “big data” anymore. (Actually, given that Dilbert already skewered big data, its heyday may already be over.)
This is the life-cycle of any good buzzword. A buzzword is born when something so new and important is happening that we need to talk about it before we understand it; while it is still amorphous. It refers to a family of related concepts. Then we develop greater understanding and distinctions, and pretty soon you’re embarrassed for your colleague when he trots out last year’s buzzword (remember Web 2.0?).
So what is the crux of “big data”? Why is it so new and important that we have to talk about it with a buzzword? In short, we’re all freaking out because old bottlenecks recently got shattered, the new bottlenecks are us and our existing tools, and mad riches are visible just over the horizon. (And it’s not just about riches — there’s also massive potential for human improvement.   )