To the layperson anxious for answers to complicated questions, the very idea of bringing together sets of disparate data and turning it into precious insights may seem like magic, a modern day alchemy, a goal placed well beyond the grasp of mere mortals. Fortunately, this is no longer the case, thanks in part to bagatelle-proportioned advances in Big Data and Big Data analytics and massive advances in imagination; we are able to look into the past, the present and the future, with absolute certainty.
To the layperson anxious for answers to complicated questions, the very idea of bringing together sets of disparate data and turning it into precious insights may seem like magic, a modern day alchemy, a goal placed well beyond the grasp of mere mortals. Fortunately, this is no longer the case, thanks in part to bagatelle-proportioned advances in Big Data and Big Data analytics and massive advances in imagination; we are able to look into the past, the present and the future, with absolute certainty.
I know some people will question my judgement in claiming that we have passed a data-driven inflection point in insight, truth and understanding, but believe me it’s true and I can back up my claims with plenty of evidence, which is to be found in many articles on LinkedIn Pulse, Forbes and elsewhere.
Nevertheless, I hear you ask, how does this work in the real world?
It’s really quite simple. All that is required is lots and lots of Big Data, an adequate sixth sense addition to predictive analytics and the simple computing power of transubstantiation. For good measure, you may want to add a smattering of over-structured data from your tired, old and abject legacy systems, but that is entirely up to you.
Now, this will work for any type of business, but it is apparently very much to the fore in the world of banking, telecoms and retail, which is what I will try to focus on.
Did you know for example that Big Data, ESP and transubstantiation can help banks to “identify, win, serve and retain customers more efficiently”? Neither did I, but apparently it is true.
Bessy Bighead, quite possibly the most well-known member of the aristocracy of Dylan’s Laugharne, is a wealthy person. However, once upon a time the financial institution she banks with assumed she was simply rich, that is, until they correlated the data they had for her in their operational systems, retail banking, family banking, investment banking and asset management, together with additional Big Data that they pulled in from Facebook, Twitter and YouTube.
Armed with Social Media, Big Data and Big Data analytics Bessy’s bank were able to put two and two together and make a billion. Now everyone is happy.
Brenda Windsor, an assiduous user of all things internet, tried to keep her identity private on the social media, the regular media and even elsewhere. Mostly in order to stop people begging her for medals and appointments and tips on how to raise corgis. Fortunately for the survival of capitalist humanitarianism, diligent data scientists armed with little more than Hadoop technology, a hunger for Big Data correlations and with an overwhelming desire for dosh, sorted her out.
Brenda, who went by the monikers of @WindsorHRH on Twitter and MadgeII on Facebook, had been rumbled. As a result, the Sex Pistols were able to re-release their smash-hit Anarchy in the UK in the knowledge that it had the blessing of the highest power in the land. We are told that Brenda, whilst not amused, did have a little chuckle. Haha!
Bobby von Drei Streifen, a little known sports apparel aficionado who spent fortunes on well brilliant adidas bling, and who also had his name changed by deed poll to show his allegiance to the brand, was a relatively unknown fellow. That is, so to
speak, until he took to social media, big time. He used the monikers of Three Stripes and Out, The Adithree am Free and Mein Cockney Scamp is a Champ, but nobody worked out that these three personas were the same guy. However, in using the power of social media, Juice Hana and adding-up numbers, the biggest opposing brands of sports clothes were able to tag Bobby with an RDIF, trace him in every mall, detect him every time he entered one of their stores and track his every action. Which in the end allowed then to promptly kick him out of, on his arse, each and every time he invaded their business space.
Using Big Data, ESP and transubstantiation data scientists were able to identify online articles and blog pieces containing toxic volumes of misleading boloney. However, because of their sworn oath of misalliance, arrogance and ignorance, nothing more was heard of the story. So all I can add is, thank god or whatever for the freedom and liberty of the western presses.
Kiss and Tell
So, you may ask, how was it humanly possible to put together all of this disparate data, with little or no idea of who was who on each and every one of the social media sites? After all, the only thing that was vaguely reliable was in the legacy systems and general ledger, right?
So, how did they make the connection? How did they manage to collect, correlate and integrate the data? After all, how can you match Brenda to Elizabeth Windsor unless you do something illegal, indecent or dishonest? Or to put it more bluntly, how does one make the connection between telephone subscriber Brenda Windsor and comments by @HerMadge on Twitter, CorgiFan on Pinterest or BuckHouse on Facebook?
Well, they couldn’t do any of this legally, could they? So, giving people the benefit of the doubt, which I really want to do, I call bullshit on these stories. That is, unless people want to pony up and admit that illegal activities involving identifying data have been going on. In that case, may the perpetrators find themselves in a grey bar Hilton in Germany. They are criminals, and I have no time or sympathy for them.
That’s all folks
Nothing much to add on this one. Apart from a big thank you for reading.
So at the end of the day, it’s not about ESP or transubstantiation, or getting gold from lead or blood from stones, but about boloney or something not entirely legal. At least, not legal in any decent society.
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