My fellow Gartner analysts just published a finalized definition of big data, and I am playing with big data visualization, or to be more precise, infographics. The difference between data visualization and infographics is that infographics does not change when data changes, consequently, data visualization is tied dymanically to the real thing, or sometimes, Internet of Things. The big data definition is 23 words, 181 characters, including spaces (big data is sparse), and contains (surprise! surprise!) 3 V’s of volume, velocity and variety.
What is really big? Is an elephant called Hadoop big? Is Walmart big? Data is twice as big as Walmart — the proof is along freeway 101 around Redwood City. For those who are not familiar with local geospatial data, Redwood City is somewhere between Oracle and Facebook, or between Lucid Imagination and Tableau, if you will. Near Informatica to be precise. This is in the vicinity where I live and from where I am intended to blog.
As we can see from my infographics (not to be confused with informatics or infonomics), this is big “data”:
Volume: an order of magnitude bigger than conventional “data”.
Velocity: it is on the freeway.
Variety: yet again, a new type of data — a billboard (non-relational, non-in-memory, no SQL).
And it has a substantial complexity aspect: taking a picture with my phone before passing the billboard. Finally, this “data” falls under the now official Gartner definition of big data, published yesterday: go check yourself!
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