BigData - Size vs. Structure

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Monash has a slightly different categorization of BigData, breaking it up into Size vs Structure.  The main idea is that while we tend to think of BigData as The Three (or Four) Vs, there is actually a distinction here between
   Size : Volume, Velocity
   Structure : Variety (,Variability)
To  quote...
  • Relational big data is data of high volume that fits well into a relational DBMS.
  • Multi-structured big data is data of high volume that doesn’t fit well into a relational DBMS. Alternative: Poly-structured big data.
  • Conventional relational data is data of not-so-high volume that fits well into a relational DBMS. Alternatives: Ordinary/normal/smaller relational data.
  • Smaller poly-structured data is data for which dynamic schemacapabilities are important, but which doesn’t rise to “big data” volume.

The point being that instead of thinking of all these in the same space, different combinations of Size and Structure refer to different categories of problems.

Its a good idea, but I think this still oversimplifies the issue - IMHO the term BigData now incorporates not just the above, but also Visualization, Analytics, Exploration, and Slicing.

In short, BigData has pretty much gotten to the point where it is nothing more than a catch-all phrase for a somewhat nebulous thing, kind of like saying Bollywood, or Korean Restaurant.


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