Horizontal Big Data

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The original (seminal?) IBM paper defining the characteristics of BigData - Volume, Velocity, and Variety

A slightly different take referring to Horizontal Big Data. The key point from the second article is

Horizontal Big Data ... has all kinds of random information that ranges from highly structured and numeric to highly unstructured.  Significantly, it tends to change quite a bit over time with increasing heterogeneity.  That’s a completely different kind of scale, and one that is not well solved by using highly structured, vertically scaling technologies.
With Horizontal Big Data ... the problem isn’t how to crunch lots of data fast.  Instead, it’s how to rapidly define a working subset of information to help solve a specific need.  The really interesting and hard part is that 100 different people will require 101 different slices.  Companies see this all the time when individuals in different departments, or across firewalls, need to share some of the information they’re working on, but not all.  I need a little bit of finance, a little bit of research, and, “oh yeah, this trend information that I found on Wikipedia.”

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