Big Data is one of those heavily abused technology terms today. It’s become a catch-all phrase used to fit any data related problem into. When the pundits defined the traits of Big Data and articulated the 3Vs, Volume, Velocity and Variety, little did we realize that the lack of clarity on whether it had to be all the 3Vs provided the perfect fertile grounds for term abuse. To add fuel to the fire, the lack of objective measures of what minimum Volume or Velocity would qualify as big data has led to the “beauty is in the eye of the beholder” syndrome, with everyone coming up with their own qualifying criteria. In fact there is a broad tendency that when it comes to the first 2 Vs, Volume and Velocity, it’s almost anything that is more than what they are currently working with that has become the criteria for justifying something as Big Data. In my opinion this was intentional (the lack of clear qualifying criteria).
Big Data and Data Science – is this hype? Print
Created by: Brian Lederman
Modified on: Tue, 9 Feb, 2021 at 6:43 PM
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