The Industrial Revolution of Data

My next genius blog idea was going to be a discussion about when tech becomes mainstream, sifting through the "next big thing" vs. the "next big nothing." Bear with me here, but I believe the point at which a technology becomes profitable is not when it becomes popular. In fact, far after that first push (thats when it becomes popular) and people start asking - but how does this make any money? An example of this is Gary Vaynerchuk's How will Twitter Monetize?

Google is another perfect example of a company who, even well after its 2004 IPO (where Google initially set their stock price at $85, to close that day over $100) folks continue to ask - but how do they make money?

You might say "advertising" and leave it at that. And you would be as right as you are vague - but right nonetheless. While that's the second most common way to make money (right behind selling something), the longer winded answer is much more interesting to me. And it's the one that gives us a real insight into the long-term plans of some of these corporate geniuses.

So what are these guys really up to?

When you look at the standards that these organizations build upon in their "spare time," the Hadoop MapReduce project comes up. So, What is it?

MapReduce is a programming paradigm that expresses a large distributed computation as a sequence of distributed operations on data sets of key/value pairs.

Huh?

The Hadoop MapReduce framework harnesses a cluster of machines and executes user defined Map/Reduce jobs across the nodes in the cluster. A MapReduce computation has two phases, a map phase and a reduce phase. The input to the computation is a data set of key/value pairs.

Huh?

A perfect example is Google's PowerMeter program, which aims to give us all a tool to measure our own energy consumption, ideally leading to lower bills and a lower collective carbon footprint. Google estimates that with access to personal energy information, each family could save 10-15% a month on energy consumption costs. The practical application from Google is to answer questions like: How much does it cost to leave your TV on all day? What about turning your air conditioning 1 degree cooler? Which uses more power every month — your fridge or your dishwasher? Is your household more or less energy efficient than similar homes in your neighborhood?

The question of "why would Google provide this information?" is answered only by imagining just how they can use the data. Keep in mind, for every bit of data Google reports to you and me, it's data they are archiving, parsing and crunching for their own use elsewhere. Besides that, this so-called "Smart Grid" of power appears to be a joint effort between Google and GE. No one said it was going to be free to join.