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Tag Archives: The Emperor’s New Big Data

Whither Big Data bullshit?

11 Wednesday Nov 2015

Posted by Martyn Rhisiart Jones in All Data, Big Data, Good Strategy, goodstrat, Martyn Jones

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Tags

Big Data, Big Data Criticism, Big Data Hype, data analytics, data-strategy, The Emperor's New Big Data

If you enjoy this piece or find it useful then please consider joining The Big Data Contrarians: https://www.linkedin.com/grp/home?gid=8338976

Many thanks, Martyn.

Pundits far and wide are hailing the end of the period of big data babble, hyperbole and bullshit and are looking forward to an epoch of practical, tangible and verifiable Big Data success stories.

Gartner themselves came out some time ago and declared that Big Data was no longer in the hype cycle. Some took this as a sign that the Big Data bullshit bonanza was over, others were more cynical and suspected a highly orchestrated ruse, a move to the next level in the game plan.

But does this new attitude towards Big Data really ring true?

Accompanying this apparent bold openness, frankness and humility in the ranks of the rehabilitated Big Data bullshit babblers there is an awful lot of what appears to be ‘more of the same’. Or as the people of Thailand might say, “same, same, but different”.

As some of you might know, I am the administrative owner of The Big Data Contrarians community group on LinkedIn, and even I was somewhat taken aback by a recent piece by Bernard Marr entitled 20 Stupid Claims About Big Data. So much so that I wrote a fairly complimentary comment on LinkedIn about it. The thing is, even as a posted it I was thinking to myself “you’ll be sorry”.

Today I read yet another Big Data ‘reformation’ piece on LinkedIn Pulse, this time from Matthew Reaney and with the compelling title of The 5 Myths of Big Data.

Call me naïve, call me illusory, and a believer in humankinds need for basic decency, but I frequently have the idea that praising moderately acceptable behaviour leads to even more good behaviour. But it was not to be, and as fast as one could say ‘what the hell is going on here?’ back came a surfeit of astroturfed Big Data bananas – from all directions – bigger, brasher and more bogus than ever before.

Make no mistake, Big Data hype hasn’t gone away, it has become more subtle, more cunning and even more misleading.

Leading the charge is the initiative to discredit Data Warehousing by all means possible, and the amount of bullshit, disinformation and blatant lies doing the rounds is beginning to look like Big Data hype reflecting Big Data itself, if only in terms of the vast volumes, varieties and velocities that this Big Data babbling bullshit comes in.

But seriously, we are simply getting more of the same, as the end of the Big Data hype war is declared, we are subject to a bombardment of Big Data boloney via Cloud, IoT, the Hadoop ecosphere (as if using Hadoop was someone linked to ecology and saving the planet), and especially this incredibly obnoxious and dopey vehicle for Big Data tripe known widely as the Data Lake – more on that stupidity at some other time. But onwards and upwards…

This all reminds me of a joke from many decades ago, retold in part from memory.

A teacher was looking for a subject about which her class pupils could write, to set as a homework exercise.

After much deliberation she decided to as ask the children to write about what they thought of the police?

Sure, not a good question, I know, and as I stated, this was many decades ago, when even grown-ups could be innocent and naïve and hopeful.

Anyway, when the children had handed in all their essays, the teacher read the essays and was disappointed to find that most of them were very wishy-washy and that the children were almost all unanimously indifferent or grudgingly respectful of the police, except for one. One of the children, let’s call him Dave, was very critical and had written “I don’t think much of the police.” When the teacher asked Dave why he had written that, he replied “All police is bastards, Miss”. The teacher was vexed by the reply, but being a good and caring teacher she considered how she could change this obviously hostile view of the bobby on the beat and the police detective taking evil doers out of circulation, so she decided to do something about it.

She had a bright idea and took her problem to the police and discussed what could be done to give the children a much more positive view of the police and the work they did, so they would see the police as a necessary part of society, to be respected but not feared.

As a result, the teacher and the police organised a police day at the school. It was a big party, with lots of free goodies, badges and posters, rides in patrol cars, sirens, interesting stories and a movie, and a big discussion with the police dog handler and his faithful and brave police-dog, Ajax. The police took special interest in Dave, he was the one they wanted to convince the most, and he was the one they made the most fuss of.

At the end of the day, the teacher again asked the children to write about what they got from the school police day that she had organised.

The following Monday, after all the essays had been handed in by the children, she sought out and read Dave’s essay, eager with anticipation.

This time it contained the surprising phrase of “I really, really don’t think much of the police.”

Again, the teacher asked Dave why he had written what he had wrote, especially considering all the effort the police had gone to in order to leave a good and lasting impression with the children in general, and Dave in particular.

He simply replied “the Police is cunning bastards, Miss.”

Personally, I have respect for the professionalism, courage and hard work of many officers in our police forces, but when it comes to my view of certain Big Data pundits – and naming no names, just watch my eyes – the feeling is not the same.

Make of that what you will.

Many thanks for reading.

If you enjoyed this piece or found it useful then please consider joining The Big Data Contrarians: https://www.linkedin.com/grp/home?gid=8338976

Many thanks,

Martyn.

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