Big Data & how to study it

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It’s 2018 and Big Data is with us and the benefits for marketing are colossal, we are collecting vast amounts of highly specific data on customer behaviour, attitudes, location and preferences, that we can then use for precise targeting. The genie is well and truly out of the bottle…

No such thing as too much data?

As our ability to harvest and store this information exponentially increases, so too does the sheer volume of data we then have to manage and sift through to extract the information we require. Astronomy is a good illustration here; In 2022 the Large Synoptic Survey Telescope (LSST) should be operational. The telescope will survey the sky for 10 years and aims to deliver 200 Petabytes of data!

A number that large is difficult to imagine, so let’s give it some context; it’s estimated that all of the written works of mankind, since the beginning of recorded history (in all languages) total perhaps just 50 Petabytes! – This example gives us an insight into the challenges Big Data presents us with.

Managing Big Data

One might reasonably think that as we collect more data, our computing power is increasing proportionally, and this true to some extent. Though if we look again at our example of Astronomy, much of the data we are collecting proves difficult for computers and AI to currently analyse. NASA’s Hubble telescope has amassed hundreds of thousands of galaxy images, and when attempting to order/classify them by shape, it turns out that the human brain is better at this task than a supercomputer.

Citizen Science

Citizen science has emerged as a fantastic method of analysing the types of data that humans are better equipped to than computers. It brilliantly engages the public (i.e: You can classify a Galaxy!) and then employs them (voluntarily) in large numbers to do the work.

This has great potential for science and medicine of course, but why limited it there. Marketing could stand to hugely benefit from clever implementation of such schemes…

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