Every now and again, I think about the vast amount of data which is at our fingertips in today’s world. This morning, I was looking for a plumber. Typing ‘plumber’ into Google gives 86 million results in less than a second. In a moment of nostalgia, I also opened the Yellow Pages – at only 128 pages of A5, I fear an older generation wouldn’t recognise what used to be a volume large enough to hold open a door. Indeed, my grandparents’ generation obtained its knowledge from books – every home had an encyclopedia. Now, every home has multiple digital devices which can access Wikipedia in the blink of an eye. You look up the largest cities in the EU, click on Birmingham, Manchester and Edinburgh out of curiosity, then on Burgh, Borough and before you know it, you’re also looking at a list of the London Boroughs, learning the difference between those with and without royal patronage… and the search goes on, an hour has easily disappeared.

Back in the day, we did not have access to enough knowledge and information. Today, we are overwhelmed by it and the challenge is to pick out the “right” information. Yet what is the “right” information? If you search for how to mend a bicycle puncture, you’ll get a number of results, some better than others, but you’ll recognise that the results, or answers, are more or less correct or right. Yet if you have a medical symptom you don’t recognise and you are foolish enough to search for it on Google, chances are you’ll find some article or other identifying a terminal illness with terrible side-effects. Is that the “right” diagnosis? Unless you’re a medical professional yourself, you probably won’t know and only scare yourself silly until you consult your doctor who will tell you the right answer. What’s the difference? There are some fields in which we are experts, others in which we are not, and a whole spectrum in-between.


It feels to me that we are currently at a point where although we have access to vast quantities of data, we have not yet learnt how to harness it. An example of this is the already clichéd term “Big Data”. Borrowing the definition from Wikipedia, “Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate”. It is clear for example in the world of transport modelling that whilst big data is out there, it is not yet refined and useful enough to be used without problems. We simply do yet have the systems in place to ‘comprehend’ the data sets and turn them into something useful, because we, our processes and our computers lack the expertise to do so. Some years from now – and from a selfish perspective I hope it will be years rather than decades – we will achieve a state whereby we will be able to request knowledge and instead of gathering a vast amount of data which will require processing, we will simply obtain the answer that we need. And I will be able to order the cheapest, most reliable plumber who can visit at a convenient time for me and fix my leak, all without a hitch.

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