Algorithms For Dummies

 

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Volume: The amount of data

 

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Velocity: The speed of data generation

 

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Variety: The number and types of data sources

 

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Veracity: The quality and authoritative voice of the data (quantifying errors, 

bad data, and noise mixed with signals), a measure of the uncertainty of 

the data

Each big data characteristic offers a challenge and an opportunity. For instance, 

volume considers the amount of useful data. What one organization considers 

big data could be small data for another one. The inability to process the data on 

a  single  machine  doesn’t  make  the  data  big.  What  differentiates  big  data  from 

the business-as-usual data is that it forces an organization to revise its prevalent 

methods and solutions, and pushes present technologies and algorithms to 

look ahead.

Variety enables the use of big data to challenge the scientific method, as explained 

by this milestone and much discussed article written by Chris Anderson, Wired’s 

editor-in-chief at the time, on how large amounts of data can help scientific dis-

coveries  outside  the  scientific  method: 

https://www.wired.com/2008/06/ 

pb-theory/

. The author relies on the example of Google in the advertising and 

translation business sectors, where the company could achieve prominence with-

out using specific models or theories, but by applying algorithms to learn from 

data. As in advertising, science (physics, biology) data can support innovation that 

allows scientists to approach problems without hypotheses but by considering the 

variations found in large amounts of data and by discovery algorithms.

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