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Organizing and synthesizing the world's energy data

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Ann Hermes/The Christian Science Monitor

(Read caption) A solar energy meter takes readings at the home of Austin resident and resource-efficient home architect, Eric Rauser in this July 2008 file photo. Big data is being touted not only as a driver of increased efficiencies for companies, but also increased revenue, Stuebi writes.

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One of the most hyped trends in high-tech is “big data”:  the accumulation, integration, synthesis and interpretation of enormous amounts of data from disparate sources.

Big data is being touted not only as a driver of increased efficiencies for companies, but also increased revenues:  as customers indicate or reveal their preferences through their behavior and choices, companies can then develop new products or services to offer in a very targeted and efficient manner to those most likely to purchase. 

With technology enabling faster mass-computation at lower cost, and a growing set of data available from all sorts of places and easily collectable from a thoroughly-connected world, big data could be a boon — especially for those industries for which cost reduction and efficiency opportunities are limited, and for companies desperately searching for new revenue streams.

Energy is a sector potentially well-suited to be mined with big data.  The industry is largely quantitative already, with scads of measured (and if not measured now, measurable) parameters across vast geographies with innumerable supply sources, processing facilities, transportation nodes, and consumption points.  And, for the most part, energy companies are largely stuck in a mode of selling commodity products, and need new twists and differentiators for which a premium can be charged.

Proactively, I went searching the Internet for the best insight, wisdom and perspective on the incursion of big data into energy.  Frankly, I didn’t find terribly much — which tells me that the space at the intersection of big data and energy is ripe for innovation.


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