Tag Archives: Martyn Richard Jones

Whither Big Data bullshit?

11 Wednesday Nov 2015

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

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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.

Stuff a great data architect should know

16 Sunday Aug 2015

Posted by in Consider this, data architecture, goodstart, goodstartegy

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Stuff a really great Data Architect should know

If you enjoy this piece or find it useful then please consider joining The Big Data Contrarians:

Join The Big Data Contrarians here: https://www.linkedin.com/grp/home?gid=8338976

Many thanks. Continue reading →

Why so many ‘fake’ Big Data Gurus?

16 Sunday Aug 2015

Posted by in Big Data, Consider this, good start, goodstart, Strategy

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Why so many ‘fake’ Big Data Gurus?

Where do you all come from?

Where do you all come from?

All your integrity’s gone

Now tell me, where do you all come from?

From ‘Where Do You All Come From‘ by Mott the Hoople Continue reading →

Consider this: Taming Big Data

01 Friday May 2015

Posted by in Big Data, Big Data Analytics, Consider this, Good Strat, goodstart

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Simply stated, the best application of Big Data is in systems and methods that will significantly reduce the data footprint.

Why would we want to reduce the data footprint?

  • Years of knowledge and experience in information management strongly suggests that more data does not necessarily lead to better data.
  • The more data there is to generate, move and manage, the greater the development and administrative overheads.
  • The more data we generate, store, replicate, move and transform, the bigger the data, energy and carbon footprints will become.

Continue reading →

Sexing up Big Data’s Dodgy Dossier

20 Friday Mar 2015

Posted by in Big Data, Consider this, good start, Good Strat, goodstart, Martyn Jones

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Most of us would probably like to work in a profession recognised for its legality, decency and honesty. At least I hope so. In my line of work, what we have right now is palpable evidence that the IT industry lacks a moral compass.

Imagine this. A major sensationalist tabloid pulls together a team of diverse journalists who are set to work on a national campaign to promote very high usage of sunbeds as a cure for cancer. Why? The newspaper owner’s son owns the sunbed franchise.

The health experts criticise the publisher for being irresponsible, unprofessional and lacking in scruples.

The public is mainly undecided, but many take the story on face value and adopt the fad. The intensive use of sunbeds sharply increases. Elsewhere, in unrelated news, the cases of skin cancer show a marked increase. Some blame it on EU legislation for bangers and bananas.

In spite of protests, the press campaign continues over many months.

Eventually, and based on the evidence of recognised health experts and bodies, the press regulatory association tries to get the offending publisher to temper their claims, but without any success. It is only when the government’s lawyers step in and threaten the newspaper owners with legal proceedings, do they freeze their campaign. Much later, the editor resigns and the board of directors issue a short apology on the back pages of their much vaunted organ.

We have that in IT. Our current sunbed cure for cancer, if you believe those who are ‘bigging it up’, is undoubtedly Big Data.

I occasionally post content to Linkedin, some of it (maybe even this piece) gets promoted through the Pulse Big Data channel. There are some reasonable pieces pinned to that channel, but unfortunately, for much of the time what we get is total and moronic Big Data astroturfing. Tantamount to the equivalent of Big Data’s very own Big Lie campaign.

The Linkedin Big Data channel reflects life, and it is full of self-aggrandising and shameless marketing guff, shot-through with scandalously flimsy promotions of tendentious success stories, specious claims of value, half-truths about realisable benefits and embarrassing conjecture about the importance of social media and internet logs.

What I am referring to mainly are superficially neutral (yet virally toxic) pieces placed in the public domain in order to promote Big Data at any cost.

Now let’s step back a bit.

For over 125 years, the Financial Times (FT) has built up a solid professional reputation for accurate reporting, reliable journalism and informative editorials. The FT is a newspaper trusted by its discerning readership and admired everywhere. In fact, I could not imagine their journalists writing about markets, securities and financial houses the same way that pundits elsewhere write about Big Data, Dark Data and the Internet of Things. Because the FT knows, that maintaining the trust of their readership is far more important than winning the short-term favours of a few market players.

So consider this; if we in IT cannot bring our standards of communicating with the public up to the levels of the financial industry, at minimum, you know what that means don’t you?

Exactly. The IT industry will have a far worse public image problem than the bankers and the solicitors currently have, and we all understand the general public appreciation of those professions.

Now, call me old fashioned, but for me that possibility is worthy of serious consideration, and especially by those in IT who confuse no holds barred pimping of fads, trends and technology, in which truth, decency and honesty are optional, for ethical, candid and informative analysis and reporting of the industry.

How will the industry take these criticisms?

To go back to the sunbed analogy what we will most certainly get comments in this vein:

Whilst those who rail against ‘the cancer curing advantages of sunbed use’ may be right – or at least partially right – the sunbed revolution will continue, just as the IT revolution industry has done, and in spite of people saying that the age of computing would be a passing mania.

So, when someone tells you “intensive sunbed use is just a dangerous fad”, what they actually mean to say is that we don’t need the term any more, as intensive sunbed use is here to stay, as are those who are shrewd, unprincipled and cynical enough to cash-in on the public’s gullibility and wilful stupidity when it comes to fads.

Yes, it does get that bad.

We have people who seemingly spend all their waking lives working out not-so-original ways and means of riddling the IT industry with vacuous bullshit, and what Big Data promotion has shown us clearly is that what we have palpable and comprehensive evidence that the IT industry in general lacks a moral compass.

Is that a reflection of IT, of those who create and manipulate IT fads, or of society in general?

Many thanks for reading.

As always, please share your questions, views and criticisms on this piece using the comment box below. I frequently write about strategy, organisational leadership and information technology topics, trends and tendencies. You are more than welcome to keep up with my posts by clicking the ‘Follow’ link and perhaps even send me aLinkedIn invite. Also feel free to connect via Twitter, Facebook and the Cambriano Energy website.

The Biggest Contradiction of Big Data

20 Friday Mar 2015

Posted by in Big Data, Consider this, good start, goodstart

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I have written at length about the fundamental contradictions of Big Data, but what I have omitted in the past is quite possibly the biggest contradiction of all. Probably because it has more to do with how Big Data is continually hyped, rather than having anything to do with Big Data as a bag of technologies – which has a whole assortment of problems in its own right.

Last time I spoke with you about the contradictions of the Big Data it was about the three Vs of volume, variety and velocity. In general, it was a view that was well received, even if not widely understood. Which of course is close enough for government work. But, get ready for “something completely different”.

If on the one hand some folk can claim that Big Data provides fact based insights and reliable forecasts of future habits, trends and preferences, then why is it so difficult to produce and socialise – yes, I like to use that term – Big Data success stories?

In short, I think we have arrived at the stage in Big Data’s cycle where it is reasonable to ask pundits to either put up or shut up.

So, why aren’t the current Big Data success fables accompanied by facts, such as names of those involved (at least businesses), the sponsors, the suppliers, the purpose of the exercise, the desired outcomes, the data used, how it is processed, what the results were, and what tangible benefits, if any, were accrued or are accruable. If that is not enough, then let people mention the technology used, the products purchased or licensed and the methodology followed.

In short, what I would like to know is why are the evangelists of Big Data telling us that bigger data is better, that more variety leads to greater insight, and that velocity is king. Why do we we told that Big Data almost assuredly results in better decisions, by people who are coy, shy or secretive about almost facts and data coming out of Big Data projects?

I have been reminded, time and time again, that there are Big Data success stories out there, and I have even been told that this information would be fully shared with me once it was agreed with the ‘clients’ that it was okay to do so. Okay, that’s fine, I know Big Data is a roaring success story (at least in people’s minds,) and I also know that it takes some time to make things up – some people are just not creative. Sure, I was told about these ‘successes’ some time ago, and you know, I’m not expecting anything that’s worth shaking a stick at, either now or later, but I’m still waiting, boys. Notwithstanding, you will still called you out as vacuous bullshitters when the time comes.

“But” I hear you cry “there is a wealth of success stories in the presses”.

Well, no, and you would wrong and gullible and foolish to think, but that is your problem, but unfortunately also mine, because this is my profession that you are playing fast and loose with.

The fact is that there is “wealth” of content that people try and pass off as legitimate Big Data success stories, but they aren’t in fact success stories, in any way, shape or form.

The thing is, people may read the blog title and even the stand-fast, but will be less inclined to actually read the article, so what remains is the impression that there are ‘loads of Big Data success stories’. But if people actually read the articles and were intelligent enough to understand them, then they would realise that inevitably there is a massive mismatch between the title of these pieces and the content. Indeed, if these pieces were actually pieces of advertising, rather than blog comments, they would be denounced in some jurisdictions for not fulfilling the advertising criteria of legal, decent and honest.

There is one more thing that Big Data evangelists (or any self-styled pundit, guru or expert for that matter) should understand, internalise and remember. If you say that you have a Big Data success story, with all the details, and that isn’t in fact the case, and it isn’t even remotely a success story or even true, then you are simply lying, and that’s deceit, it’s unprofessional and it’s unethical, and you are a scoundrel. So live with or fix it, the choice is yours.

Many thanks for reading.

Big Data’s Virtuous Circus

20 Friday Mar 2015

Posted by in Big Data, Consider this, data management, good start, goodstart

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Many people come up to me in the street and ask me what Big Data is all about. It has happened to me so many times in the past that I am convinced that it might just happen to you as well. I know sort of thing, I read the Big Data tealeaves. Nothing gets past me.

The first time a complete stranger came up to me in public and said “Hello, will you tell me what this Big Data lark is all about then?” I was lost for words, you just ask my Aunt Dolly, he can vouch for that, no problem. Later that day I read a book – it was my dad’s book – and I then decided to adopt a strategy.

Therefore, in the spirit of springtime goodwill to all men and women, I have put together this blog piece in that hope that it will enlighten, help and entertain.

What is big data?

Big Data can be characterised by the 10 Vs – yes, 10, not 4. Which, in my book, is more than enough to bring up-to-speed the average Big Data John or Jane that one meets on the street, and who naturally wish to be informed of such matters.

In layperson’s terms this a series of landmarks and pointers in the analytics space used to frame and guide the didactic aspects of Big Data.

The fundamental Vs of the Big Data canon are these:

  • Vagueness
  • Volume
  • Variety
  • Virility
  • Velocity
  • Vendible
  • Vaticination
  • Voracity
  • Vanity

So, let me now explain what each of these characteristics mean to those who might know and for those who might want to know.

Vagueness: This is perhaps the trickiest of questions to address, given the vast panorama that is cast before this incredibly complex yet easily graspable concept. But let me state this, and let there be no mistake about it. At this point in time, what makes Big Data vague is also what makes Big Data specific, explicit and certain. That is to say, in order to ‘come to an understanding’ of Big Data, it is necessary to completely embrace the dialectic of knowing the unknowable. So belief is an absolute essential element – belief and data, that is.

Volume – If there ever was a time to “pump up the volume”, we have it here with Big Data.

Big, voluminous, gorgeously rotund and infinite. Big Data is called Big Data because there is a lovely, roly-poly, likeable never-ending load of it. Its volumes can be measured in zeta-bytes, which you can be assured, is a helluva lot of data.

Variety – As they might say down my way, “variety is the spice of life, innit”. This is what makes Big Data so special. So appealing.

Because before Big Data there was absolutely no variety in anything, at all. We lived in a bland world, bereft of detail, nuance and diversity. Nothing could be measured, analysed or explained, because we lacked Big Data. We were ignorant. So ignorant and stupid that we couldn’t see the sense of putting the diapers next to the beer, or of offering three for the price of two.

Fortunately, today this is no longer the case if we don’t want it to be, and thanks to Big Data we have a veritable sensorial explosion. No longer is IT just a couple of symbols scribbled in crayon on someone’s school notebook.

Virility – Move over Smart Data, the new kid on the block is Big Data.

If Big Data were described in the manner of a religious text, it would be accompanied by a never ending narrative of begets.

So, what does that mean?

Simply stated, Big Data creates itself, in and of itself. The more Big Data you have, the more Big Data gets created. It’s like a self-fulfilling prophecy in 360 degree, high-definition, poly-faceted and all-encompassing knowing. The sort of thing that governments would pay an arm and a leg to get their mitts on.

Velocity – Velocity is of the essence. Velocity kills the competition. More velocity, less haste.

We demand that service is ‘velocious’. ‘Everything’ must be ‘now’, or it’s too late.

This means we need to be able to handle Big Data at velocity – at the speed of need.

Charles Babbage once stated (or maybe it was more than once) that “whenever the work is itself light, it becomes necessary, in order to economize time, to increase the velocity.”

But remember, we are dealing with mega-velocity here, so don’t drink and drive the Big Data Steamship, Star-ship or Mustang.

Vendible – If you can sell it, and sell it as Big Data, then it ‘is’ Big Data. If you can’t, then it’s not. The saleability of Big Data proves its existence.

So, what are the vendible aspects of Big Data?

Let’s leave that easy question for another day. But for now I can confidently state that it is used to mobilise armies of commentators, industry analysts, publicists, punters, writers, bloggers, gurus, futurologists, conference organisers, conference speakers, educators, customer relationship managers, salespeople, marketers and admen.

Vaticination – Edmund Burke is down on record as stating that “you can never plan the future by the past”. Now Burke may have been a clever person when it came to many things, but he wasn’t exactly a whiz when it came to Big Data.

There are people in the world who are in no doubt that Big Data provides the sort of visionary and predictive powers only previously obtainable through ritual sacrifice, magic potions and the casting of spells. Others are highly critical of the understatement implicit in this belief.

For many, Big Data will make the Oracle of Delphi look like a mere call centre.

This is why the power of vaticination plays a characteristically important role in the world of Big Data.

Voracity – This is based on the quasi-rationalist argument that Big Data is big and it has an omnipresent and insatiable self-fulfilling desire.

Big Data comes with an attendant requirement for hardware, even if it is a whole load of consumer hardware tacked together in a magnificent and miraculous mesh of magic.

Big Data can be characterised by voracity, but this comes hand in hand with the ‘ventripotent’ IT industry.

Veracity – The eminence of the data being captured for Big Data handling can vary significantly. The quality or lack of quality of the data naturally has the potential to impact the accuracy of analysis using that data.

Before Big Data arrived on the scene we knew nothing about Data Quality or data verification. This is why ETL and Data Cleansing tools lacked the power to effectively quality check and verify data, to ensure that any erroneous or anomalous data was rejected or flagged.

But now, with the sophistication of tools such as ‘grep’ and ‘awk’ at our disposal, we have the power in our hands to ensure nothing ‘dodgy’ gets into the analytical mix.

Vanity – In my opinion, to fully grasp the underlying and profound meaning of Big Data, it is essential for us to understand the difference between vanity and conceit. Max Counsell claimed that “Vanity is the flatterer of the soul”. Goethe characterised vanity as being “a desire for personal glory”. After an incident with an Anarchist (presumably a Big Data Anarchist), Blackadder remarked to Baldrick that “The criminal’s vanity always makes them make one tiny but fatal mistake. Theirs was to have their entire conspiracy printed and published in plain manuscript”.

That’s all folks!

So that ends the brief rundown of the defining characteristics of Big Data.

So, to summarise. That, which has passed before, necessarily divulges both the upside and downside of Big Data. By reaching out, opening up the kimono and relating the 10 Vs we are disclosing that which cannot be disclosed, exhibiting the absence of essential essence, and thereby opening up the entire field, discipline, profession, science and art to examination, questioning and ridicule.

Many thanks for reading.

7 Signals that someone has quit

14 Saturday Mar 2015

Posted by in Consider this, good start, Good Strat, goodstart, Martyn Richard Jones

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You are the boss. You are the leader, coach and manager, and there are some things that you just got to learn, like it or not. One of these skills is to be able to identify when someone has quit. “How dare they?” I here you ask.

The first time I quit a job and didn’t tell anybody was when I was in the RAF working as a fighter pilot in World War 2, and I accidentally bombed Newport in South Wales, and was given a stern talking to for my troubles. Well, I didn’t actually quit and I was never in the armed forces and I was born into the era of the Beat Generation, but that’s by the by, it’s just there for effect, to create some artificial empathy between me and those who have actually quit a job and not told anyone about it. Myself, I would never do such a thing. Although to be fair, Newport has looked like it has been freshly bombed with dark green, brown and grey shades of poster paints and self-raising flour, since forever. Continue reading →

Consider this: Big Data Forever!

14 Saturday Mar 2015

Posted by in Big Data, Consider this, dark data, Martyn Jones

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Dans ce pays-ci, il est bon de tuer de temps en temps un amiral pour encourager les autres – Voltair

My gran used to tell me that honesty pays. Of course, she never really understood banking or IT, probably because she didn’t want to know anything about them, and she never lived to witness the amazing hype circuses, the spin doctors spiel or the focus-group dog-and-pony show of the 21st century. Indeed, if honesty were a guaranteed payer my gran would have amassed more wealth than even Warren Buffet himself.

If my gran lived today, she might reflect on what Big Data might be about – maybe she would even consider it benignly, as a sort of shelter for fallen men of once uncertain virtue. We will never know. So onwards and upwards.

The Harvard Business Review contemplated honesty in somewhat different terms:

“Honesty is, in fact, primarily a moral choice. Businesspeople do tell themselves that, in the long run, they will do well by doing good. But there is little factual or logical basis for this conviction. Without values, without a basic preference for right over wrong, trust based on such self-delusion would crumble in the face of temptation.”

In a marvellous book, A few good from Univac, David E. Lundstrom narrates the story of Sperry Univac in the 1960s, one of the true great innovators in the first forty years of IT, and includes an allegory taken from the engineering front-line. I will recount it here, edited to highlight the zeitgeist, for your entertainment and as Voltaire put it, “to encourage the others”:

In the beginning was the Big Data Plan.

And then came the Big Data Assumptions.

And the Assumptions were without form.

And the Plan was without substance.

And darkness was upon the face of the Workers.

And they spoke amongst themselves, saying: “It is a crock of shit, and it stinketh.”

And the workers went unto their Supervisors and said: “It is a pail of dung, and none may abide the odor thereof.”

And the Supervisors went unto their Managers, saying: “It is a container of excrement, and it is very strong, such that none may abide by it.”

And the Managers went unto their Directors, saying: “It is a vessel of fertilizer, and none may abide its strength.”

And the Directors spoke amongst themselves, saying to one another: “It contains that which aids plant growth, and it is very powerful.”

And the Vice Presidents went unto the President, saying unto him: “This new plan will actively promote the growth and vigor of the company, with powerful effects.”

And the President looked upon the Big Data Plan, and saw that it was good.

“But?” I hear you say, “why fight it, why not take advantage of the Big Data zeitgeist?”, “Why not cash in on the grand bonanza Big Data bandwagon?” or “Monetise the 3 three famous Vs of Big Data?”

Well, it had crossed my mind, briefly, and (outside of the USA) we’ve all done stuff we have not entirely believed in, so the temptation to cash in is present, capisci? This paraphrasing of a piece from My Blue Heaven might give you a better idea:

One of my best friends makes his living as a completely phony Big Data Scientist. For two hundred bucks he can make you a Data Scientist or a Big Data guru. Some guys give you an education but this guy gives you immediate access to high paying jobs, sex that would make the 256 trillion Shades of Blah blush and a life in the City, the Big Apple or a small town in Germany.

Moreover, for an extra 250 bucks (limited time offer) you can also become a certified Big Data Neuro Trainer, which will allow you to do unto others what has been done unto you.

I also considered Big Data Brokerage, Big Data Certification and Big Data Independent Trading (New York – Paris – Peckham). The opportunities are immense.

However, what happens when the Big Data well runs dry, and I (and many others get tarnished with the mark of Big Data) become pariah by complicity, collusion or simple association?

That question I will leave for another day. But just consider the following.

All right, I admit, I am a big long-time fan of comic genius Mel Brooks, who has a knack of capturing deep insight from the human condition, especially when the human condition is off guard and shallow. In that vein, this is how I like to think the dialogue from the Dole Office scene from The History of the World Part Two would have gone, if he were to write that today:

Dole Office Clerk: Occupation?

Data Magnus Comicus: Stand-up Big Data scientist.

Dole Office Clerk: What?

Data Magnus Comicus: Stand-up Big Data scientist. I coalesce the vaporous datas of the human interaction with the social-media networking, Internet of Everything, and always-connected experience into a… viable, analytical and meaningful predictive-comprehension.

Dole Office Clerk: Oh, a Big Data bullshit artist!

Data Magnus Comicus: *Grumble*…

Dole Office Clerk: Did you bullshit Big Data last week?

Data Magnus Comicus: No.

Dole Office Clerk: Did you try to bullshit Big Data last week?

Data Magnus Comicus: Yes!

Finally, I leave you with some wise words from Israeli American professor of psychology and behavioural economics, Dan Ariely:

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”

Many thanks for reading.