Big Data has reached a tipping point. It is now officially the hot new technology industry of the second decade of the 21st century. And there were 70,000 witnesses to the moment it happened.

How do you know when a new technology becomes cool? When everybody who is anybody in tech feels obliged to attend its trade show.

The hottest tech trend of the year is Big Data, the application of powerful new analytical tools to the mountains of data now being created by the Cloud and by millions of new sensors embedded into the natural world.

Big Data, the application of a new breed of analytical tools to the vast caches of data being produced by computers and other forms of technology, is on the brink of becoming a household word – thanks to new books, conferences and articles that are slated to appear over the next few months.

But as impressive as these Big Data stories will be – and many of them, like mapping the insides of F5 tornados, tracking every patient heartbeat over a lifetime and predicting the behavior of consumers from millions of store purchases – the real story is unlikely to be told.

For decades we have been focusing on the architecture of data; now the time has come to turn our attention to the economics of data. . .

It is a tired cliché that Silicon Valley and high tech revolution resemble the 1849 California Gold Rush. But, at the dawn of the Big Data era, that analogy may be more true than ever. . . not to the Gold Rush itself, but to what came immediately thereafter.

One of the great things about the blogosphere is that you are allowed to change your mind.

In my last blog I defined Big Data as any body of information that is so big it cannot be analyzed directly for profitable use in its raw form. Since I wrote that I’ve had a number of conversations with Big Data providers, tool-makers and users, and I’ve come to the conclusion that my definition was a bit too facile – and insufficiently empirical. So let’s try it again:

Big Data is any data that requires massively parallel computational techniques to handle.

Along with medical applications and geography-based social networks, “Big Data” is the hottest topic in tech these days. Everyone seems to be talking about it – though if you listen closely you’ll realize, as is often the case with new technologies, that nobody really knows what it is.

If ever there was an application designed for cloud computing, it is healthcare. I’m convinced that any attempt – from free enterprise to government-managed – that has a chance of actually fixing our current healthcare crisis will have to go through the cloud.

If you follow the world of enterprise software, you’ve no doubt noticed that the last couple months have been a time of frenzied acquisition of little fish by big fish. IBM bought DemandTech for $440 million, Oracle purchased RightNow Technologies for $1.4 billion, and in the biggest deal of all, SAP snapped up SuccessFactors for $3.4 billion. These moves harken back to a similar burst of acquisitions by these same players in 2007.

When I was boy, if your parents wanted to buy a stereo music system to play the family LPs, they had basically two choices: component or console. And they were very different indeed.

In the tech world, as with the rest of the business world, we use terms like “attack”, “capture”, and “defense” and other martial terms to describe the endless challenge of gaining customers, hanging on to them over time, and growing them into ever-more profitable sources of revenue.