Iii) Messiness

Sometimes there is a trade off between accuracy (more errors) in return for scale and identifying general direction of trends, rather than knowing the exact phenomena, ie willing to sacrifice a bit of accuracy in return for knowing the general trend

"...sometimes 2+2 can equal 3.9 and that is good enough..."

John Forrester as quoted by Victor Mayer-Schonberger et al, 2013

"...Simple models and a lot of data trumps more elaborate models based on less data..."

Peter Norvig (Google) as quoted by Victor Mayer-Schonberger et al, 2013

Big Data transforms figures into something more probabilistic than precise

Looking at significantly more data helps us handle the desire for exactitude, ie with less error from sampling, we can accept more measurement error. Until recently digital tools were premised on exactitude, ie the database engines would retrieve the records based on perfectly matching an inquiry, ie precision was important. Remember: as scale increases, so does inaccuracy. For example, a small stall can count the money in the cash registers each night at the end of business down to the last cent; however, the country' gross domestic product calculation will not have the same accuracy as the small stall!!!!

"...What we lose in accuracy at the micro level to gain insight at the macro level......We are leaning in favour of more and messy over fewer and exact..."

Victor Mayer-Schonberger et al, 2013

We do not focus on causality. Instead we discover patterns and correlations in the data that offer us novel and invaluable insight. Correlations may not tell us precisely why something is happening, but they alert us to what is happening.

"... Big Data is about what, not why......we let the data speak, we can make connections that we never thought existed. Hence some hedge funds parse Twitter to predict the performance of the stock market. Amazon and Netflix base their product recommendations on a myriad of user interaction on the sites. Twitter, LinkedIn and Facebook all map uses of 'social graph' of relationships to learn their preferences..."

Victor Mayer-Schonberger et al, 2013


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