Big Data: Just because you can doesn’t mean you should!

Category: Blog

By Janice

30/09/2015

Information technology has always been full of buzzwords and jargon. It can be disconcerting for those that consider themselves non-technical and also for technical people too. Big Data is everywhere these days. So what does it really mean?

The Wikipedia definition is ‘…data sets so large or complex that traditional data processing applications are inadequate.’ So the meaning is pretty straightforward – big data is huge amounts of data being created by everyone and everything. The challenge is what to do with all this data that’s being pumped out on social media, mobiles, RFID tags etc.

Technologists are good at rising to a challenge and there are any number of tools and products available to analyse the data to spot trends, link things together and so on. However that’s just it, these are tools that are predicated on the assumption that we want to access all this data. My fear is that we are in danger of going for quantity rather than quality.

There is also a danger that the data starts to manage us rather than the other way round. If we automate management of data and use scrapers –how true are the results? In many cases we just end up with a lot of rubbish which teams spend weeks trying to distil down into something sensible.

IT people have always been creative and inventive and hell bent on solving problems – even ones that don’t exist. Many years ago I learned an interesting lesson – just because you can doesn’t mean you should. I wrote an incredible piece of code that did some management around work orders. I created some some tricky little subroutines and I had written a brand new function. However when I showed the end result to the engineer, he was clearly puzzled. Eventually he told me that it looked great but it was of no practical use to him whatsoever!

So getting back on track and to Big Data. Let’s be sensible about what it is and how we will use the data. Please let’s make sure that what we are doing really has value and let’s not sacrifice quality for quantity.

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