This post was co-authored by Roger Ehrenberg, founder and managing partner at IA Ventures.  A variation of this post was published by the GigaOm Media network.

The tar sands of Alberta, Canada contain the largest reserves of oil on the planet. However, they remain largely untouched, and for one reason: economics. It costs as much as $40 to extract a barrel of oil from tar sand, and until recently, petroleum companies could not profitably mine these reserves.

In a similar vein, much of the world’s most valuable information is trapped in digital sand, siloed in servers scattered around the globe. These vast expanses of data — streaming from our smart phones, DVRs, and GPS-enabled cars — require mining and distillation before they can be useful.

Both oil and sand, information and data share another parallel: in recent years, technology has catalyzed dramatic drops in the costs of extracting each.

Unlike oil reserves, data is an abundant resource on our wired planet. Though much of it is noise, at scale and with the right mining algorithms, this data can yield information that can predict traffic jams, entertainment trends, even flu outbreaks.

These are hints of the promise of big data, which will mature in the coming decade, driven by advances in three principle areas: sensor networks, cloud computing, and machine learning. (more…)