Figure. 01[i]
Donald Trump’s surprise victory in the U.S election has tossed polling experts into a genuine shock, but for a little-known British company, ‘Cambridge Analytica[ii]’ it is confirmation that their data analysis is indeed working. It is the use of big data by Cambridge Analytica that is in question. The fact that people are being secretly monitored without their consent, and the information is being sold onto political parties.
So, what is big data, and what impact can it have?
Everyone consumes information in some form or the other, and with every passing day the amount and size of this information is growing making it impossible to process. This is precisely the reason we’re shifting to the use of big-data; a term that refers to things that can be done at a larger scale.
Viktor Mayer-Schönberger and Kenneth Cukier in their book Big data: A revolution that will transform how we live, work, and think, claims that ‘‘There is no rigorous definition of big data. Initially the idea was that the volume of information had grown so large that the quantity being examined no longer fit into the memory that computers use for processing, so engineers needed to revamp the tools they used for analyzing it all.’
Although we are just at the beginning of big data, we depend on it every day. We use Amazon that can recommend the ideal book for us to read, dating sites to pair up couples based on their attributes, so is it justified to say big data is about predictions? To validate big data, Viktor and Kenneth have explained the concept via 4 major points. Let’s examine them below.
1- From some to all
Without comprehending what to search for, one would have no clue what test to utilize hence losing out on information from sampling.
An example of this is of Xoom, a firm that specializes in international money transfers. In 2011, Xoom identified a higher than average number of Discover card transactions originating from New Jersey. Upon closer inspection, a pattern was discovered that indicated criminal activity. The best way to detect the irregularity was to analyse every one of the information—testing a limited number of transactions would have missed it.
2- Messy
Our ability to use all available data is possible but at a cost of allowable errors. Meaning that as the level of data being accessed increases, so do the chances of the data being infected with impurities such as the information not aligning perfectly due to being from various sources.
It is a trade-off. By being able to generate more data that can give us the bigger picture, we must relax the standard of errors. As Forrester, a technology consultancy, puts it, “Sometimes two plus two can equal 3.9, and that is good enough.”
3- Correlation
Predictions grounded on correlations lie at the heart of big data as Viktor and Kenneth explain. For example, a prediction can give us a head up that the sale of Pop-Tarts will increase ahead of a storm giving stores like Wal-Mart a chance to stock up but it may not be able to build a relation between Pop-Tarts and a storm. The relationships indicate what, not why, but rather as we have seen, recognizing what is regularly sufficient.
4- Datafication
Datafication is a modern technological trend turning many aspects of our life into computerised data and transforming this information into new forms of value.[iii] Without having an analytical value, the data is just another set of words. For example, if Facebook hadn’t datafied relationships using the social graph, it would just be another set of information that didn’t hold much importance.
Nowadays, it is possible to collect data without much exertion or even mindfulness with respect to those being recorded. The price of holding data has also fallen, making it an easier task to fulfil the demands of online advertising but at a cost of shifting from ‘privacy by consent’ to ‘privacy through accountability.’ In simpler terms, it is the idea of holding people in charge for something they haven’t done in real, but on what is predicted they would do in the FUTURE.
To sum it up, big data is something that has given us unimaginable benefits, but like all good things, it comes at a cost.
References
Mezzofiore, G. (no date) How a little-known data firm helped trump become president. Available at: http://mashable.com/2016/11/10/donald-trump-polling-data/#RJG31YQSQSq2 (Accessed: 4 December 2016).
Mayer-Schönberger, V., Cukier, K. and Mayer-Schonberger, V. (2013) Big data: A revolution that will transform how we live, work, and think. Boston: Eamon Dolan/Houghton Mifflin Harcourt.
[i]https://www.google.co.uk/search?q=donald+trump+victory+funny&rlz=1C1PRFE_enGB705GB705&espv=2&biw=1242&bih=602&source=lnms&tbm=isch&sa=X&ved=0ahUKEwilvP_C19vQAhULAcAKHU7QBdEQ_AUIBigB#imgrc=ITZ11zCKOSZcTM%3A
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