PolySpot Utilizes Data from both Past and Present to Offer Insights

February 1, 2013

A very interesting article came out of Wired recently. This piece, “Stop Hyping Big Data and Start Paying Attention to Long Data,” asserts that perhaps living in real-time and considering only current snapshots may be a flawed method.

Analytics should look at both slow changes, throughout longer periods of time and fast changes happening in real-time. The author refers to slow changes as “long data.”

The article states:

By “long” data, I mean datasets that have massive historical sweep — taking you from the dawn of civilization to the present day. The kinds of datasets you see in Michael Kremer’s “Population growth and technological change: one million BC to 1990,” which provides an economic model tied to the world’s population data for a million years; or in Tertius Chandler’s Four Thousand Years of Urban Growth, which contains an exhaustive dataset of city populations over millennia. These datasets can humble us and inspire wonder, but they also hold tremendous potential for learning about ourselves.

This is an article in which the angle made the story. No one says big data and implies that the historical contexts and perspectives are not included within that terminology. Big data solutions such as PolySpot are utilizing data from across every sector of the enterprise, both past and present, in order to deliver effective information on the future.

Megan Feil, February 1, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search.

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