Martyn Richard Jones

Lora del Rio, 2nd February 2017


post-truth – ADJECTIVE – Relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief.

fake news – a type of hoax or deliberate spread of misinformation in social media or traditional news media with the intent to mislead in order to gain financially or politically.

Big data – a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them.

If we believe the presses, and who wouldn’t, we are living in an age of post-truth, fake-news and Big Data.

Actually, none of this is new, not even the amazing volumes, varieties and velocities of boloney that surrounds the Big Data bandwagon. In fact, the big porky technique (a.k.a. the big lie) was invented when Anglo-Saxon cynicism was in its infancy.

What’s more, it’s quite ironic that the biggest use of Big Data is to promote the design, manufacturing and distribution of even more post-truth fake-news, much of it to promote Big Data.

Just take LinkedIn as an example in a million. On the highly venerated Pulse platform there have been hundreds of articles on Big Data that are the epitome of fake-news and post-truth, and many of them are from the same sources.

In fact, social media in general is so caught up in its love affair with this nebulous thing called Big Data (actually it’s just hardware and code), that anything that detracts from the “Big Data is the next big thing” mantra, is systematically side-lined, buried or rubbished.

In short, if you are not on message with the Big Data boloney then you will be subject to censure.

Don’t believe me? Answer this then. How come no negative press gets promoted on LinkedIn’s Big Data channel these days?

Just follow the money. The Big Data channel is controlled, thanks to LinkedIn’s perverse forms of control, by those who have a vested interest in ensuring that any and all dissenting opinions about the amazing Big Data fad are well and truly buried.

Who has a say on what gets promoted on the Big Data channel? That’s right, the biggest spreaders of drivel-based Big Data flim-flam this side of Kansas.

The other day I came across an advert for a book, the ostensible purpose of which was to detail some amazing Big Data success stories.

I can’t remember now if there were 4.5 amazing success stories or 45 million amazing Big Data success stories, but, that’s beside the point, as (apart from Google, Amazon, Twitter and Facebook) hardly any of these amazing Big Data success stories touted by this, that and the other hustler are actually tangible, coherent and verifiable Big Data success stories, and many of them are simple cribs of Data Warehousing, VLDB and Business Intelligence success stories – with the names changed.

The thing is, when these amazing Big Data success stories are immediately and easily debunked, there is usually a small subset of the sycophantic army of believers who will stand up to try and defend their Big Data gurus.

Instead of making a credible case for big data by simply providing coherent, cohesive and verifiable details of Big Data success stories, the unhappy Big Data bunnies take a different tack – for obvious reasons.

I get told:

  1. There are plenty of Big Data success stories, you just don’t see them
  2. That I don’t understand Big Data technologies, and
  3. That I prefer the old fashioned approaches of quill, ink, blotting paper and ledger books.

Smitten detractors of my criticism of Big Data, and that’s what they are, avoid any mention of the dearth of coherent, cohesive and verifiable details of Big Data success stories, or neither do they make any attempt to put some meat on the ethereal bones of Big Data success stories.

The second tack taken by the Big Data fan club is to claim that those sceptical of the amazing Big Data claims are simply naïve, unqualified and ignorant.

The thing is, Big Data technology is not complicated, it isn’t a secret and there’s nothing in it that is actually novel, exciting or innovative in pure software or data engineering terms. Unless of course you are somebody who thinks that providing white earphones for an iPlayer was the height of technological innovation.

The third item mentioned is that in spite of the best efforts of Big Data acolytes to paint Big Data sceptics as Luddites (and, I have nothing against Luddites per se), the argument is babble, since the aged, brute-force and relatively unsophisticated approach to list creation and counting, isn’t that new and isn’t that smart and in many cases it certainly isn’t as uniquely cost-effective as it is touted to be either. Moreover, it doesn’t even replace anyone with a machine – it just takes up time, money and patience – and worst of all, deflects attention away from more important initiatives and issues. So, no. Nothing to do with Luddites at all.

Nothing to do with ignorance of Big Data, nothing to do with clinging to the past, and, nothing to do with a refusal to embrace the new. It’s about pointing out amazing Big Data success stories that don’t deliver on their promise. It’s about calling bullshit on bullshit and the bombastic clowns who spread it.

Now, if there’s a cost-benefit advantage to be had, and the answer is Big Data technology, then one would simply use it. Naturally.

Many thanks for reading.

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