Peter Steiner's cartoon (Photo credit: Wikipedia)
The Internet’s been around since 1969, the web since 1990. I was one of the first 5,000 people on the Internet, back in 1971, when they were giving accounts to students at schools (like UCLA, Harvard, MIT, CMU, Stanford) involved in developing the network that linked the 69 (yep, count ‘em, 69) sites on the Net. ARPA, the DoD Advanced Projects Research Agency, which was paying for the whole thing, also had a few sites in that bunch of 69. Those mostly had design specs for the Net, which everyone on it already had. There just wasn’t much traffic.
The reason they gave accounts to lowly undergrads was to generate some traffic to see if the damned thing worked. There wasn’t much to do besides pass around the UNIX joke file and peruse the generally sparse digital archives offered. But there were lots of undergrads with email, and the UNIX jokes never die, so it worked.
But nobody, anywhere, ever seemed to care even a fempto-iota what was in your emails or which sites you visited. This lack of interest continued during the early days of the consumer Internet. One of 1993’s most popular cartoons, by the New Yorker’s Peter Steiner (which would be called a meme now), showed two mutts in front of an old style CRT. One says to the other “On the Internet, nobody knows you’re a dog.”
Now, not only do they know you’re a dog, they know your size, preference in kibble, chew toys, and if you have fleas. It may sound small, but it’s in the Big Data-verse. For a partial list of the Big Data they have about you, click here.
There are so many kinds of “Big Data” people talk about that it’s hard to tell the players without a program. Lots of us, including me, are trying to figure out the “Big Data Landscape.” My fellow Forbes contributor Dave Feinleib has published a handy map. I visited many of the websites, and this is a vast technological territory.
My last post ("Speed Is Making The Market Dangerous. Nascar Shows How We Can Make It Safer.") was about the kind of big data produced in financial markets. People are interested in that because of the perceived value in it. But if we measure by entrepreneurial energy, especially in Silicon Valley, there is more perceived value in the new flavor of Big Data than the old.
This idea was particularly vividly stated to me by George John, the CEO of Rocket Fuel, a fast-growing Big Data science firm in the Valley. George, and his lead quant jock, Mike Benisch, both have quant investing cred, having worked on Wall Street, and read “Nerds on Wall Street," and they invited me over for a visit.
George’s insight is that “Big Data is the New Quant Investing,” and the more I think about it, as a longtime quant investor, the more I think George is right. Many of the ideas from quant investing make sense in this context; histories are huge, and experimentation is easy. There’s an underlying behavioral model, plus, you know your counter-parties. The large volume and variety of data allows use of new “data voracious” statistical and machine learning methods that, in finance, are useful for high-frequency trading, but are worthless on daily or monthly market data. It's words as well as numbers, so natural language tools can work along with numerical calculation.
A jumbo bowl of quant chow for sure.
