Tag Archives: Big Data Criticism

Big Data: And the Hype Played On

10 Thursday Dec 2015

Posted by in Big Data, Big Data Analytics, business strategy, Good Strat, Good Strategy, goodstrat, Inform, educate and entertain., IT strategy, Marty does, Martyn does, Martyn Jones, Martyn Richard Jones, Strategy, The Amazing Big Data Challenge, The Big Data Contrarians, Uncategorized

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MARTYN RICHARD JONES

Despite the best efforts of Hadoop evangelists, consulting houses, and IT infrastructure and service vendors, Big Data – hailed as the greatest thing since the dawn of greatest things – is failing, and dramatically so, to produce the necessarily corresponding quantity and quality of tangible, detailed and verifiable success stories.
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The Banality of Big Data Hype

05 Saturday Dec 2015

Posted by in Big Data, Good Strat, Good Strategy, Inform, educate and entertain., Martyn Jones, Martyn Richard Jones, Rant, Uncategorized

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Nauseated by the non-stop crap, railroading and bullying tactics from a reduced group of snotty little techno bastards? Disgusted by the crass propaganda, crude instrumentalisation and fetid boloney from the likes of Bernie, Vinnie, Spats and an attendant entourage of snake-oil merchants and  brain-dead sycophants? Sick and tired of the amazing, incredible and fabulous velocities, varieties and volumes of  Big Data bullshit washing the decks of the SS LinkedIn? Well, be sick and tired no longer. Here is the antidote!

Some interesting Big Data facts to think about this weekend.

I. More Big Data bullshit has been created in the last couple of years, than in the entire history of humankind.
II. Big Data bullshit will grow faster than ever before, in spite of what Gartner say to the contrary.
III. By 2021, if the mega-trending nonsense does not go unabated, there will be 40 megabytes of Big Data bullshit created for every living woman, man and child, every sixty seconds.
IV. Also, in 2021 the accumulated digital universe of Big Data bullshit will grow from 8 spartabytes to 22 marrsabytes.
V. Every second people are thinking about creating new Big Data bullshit. For example, 20 million search queries alone (per minute) are generated with the sole intent of creating even more Big Data bullshit. This is set to grow to over 100 thousand brazilian bulslhit queries per year by 2020.
VI. Every minute an estimated 280 hours of Big Data oriented porn is uploaded to the ‘next greatest thing since sliced bread and butter pudding‘ network.
VII. By 2017 over 1 trillion Big Data bullshitters will be connected via Facebook.
VIII. Facebook usage by Big Data bullshitters will make the current social media scene look like a walk in the bullring.
IX. In 2015, an astounding 1 million trolleyloads of photos were uploaded to the web every single hour of the day. By 2017, nearly 80% of photos taken will include a cameo by one or more smartass Big Data bullshit artist.
X. This year, over 4 billion smartass Big Data bullshitters will be shipped – all packed with communication devices capable of collecting and communicating all kinds of Big Data bullshit, not to mention the Big Data bullshit the amazing Big Data babblers create themselves.
XI. By 2020, we will have over 8 billion Big Data idiot savants (overtaking sentient and rational human beings).
XII. Within five years there will be over 5 billion Big Data smartasses connected in the world, all developed to collect, analyze and share Big Data bullshit.
XIII. By 2020, at least a third of all Big Data bullshit will pass through the bullshit cloud (a network of Big Data bullshit servers connected over the Big Data bullshit Internet).
XIV. Distributed Big Data bullshitting (performing Big Data bullshitting tasks using a network of computers in the cloud) is very real. Google uses it every day to involve about 10 Big Data bullshitters in answering a single search query, which takes no more that 0.2 weeks to complete.
XV. The Hadoop Bullshit Ecosystem (open bullshit software for distributed bullshitting) market is forecast to grow at a compound annual growth rate 299,258% surpassing $111 billion by 2021.
XVI. Estimates suggest that by better integrating Big Data bullshit, we could save as much as $300Bn a year on smoking, drinking and having a wild time. That’s equal to reducing costs by $1000000 a year for every person on earth.
XVII. The White House, who first recognized Big Data as the bullshit it is, has already invested more than $200 in big data bullshit projects.
XVIII. For an archetypal Fortune 1000 company, just a 10% increase in data accessibility will result in more than $650 billion additional net income.
XIX. Retailers who leverage the full power of big data could increase their operating margins by as much as 36,660%
XX. 173% of organizations have already invested or plan to invest in big data bullshit by 2099.

Many thanks for reading. Think about it. I hope you get the message.

The Big Data Shell Game

11 Wednesday Nov 2015

Posted by in All Data, Big Data, Cloud, Data Lake, data science, Inform, educate and entertain., IoT, Martyn Jones

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To the experienced observer, Big Data propaganda may well appear to be a disorganised surfeit of half-truths, sleights of hand and boloney. Indeed, the once famously alliterative characterisation of Big Data as defined by volumes, variety and velocity, seems now more appropriately applied to the quantity, invariability and quality of the incessant self-aggrandising hype, hokum and Hadoop being astro-turfed by every dog and his guru. Indeed, the very fact that such an inevitable mega-trend needs so much hype, disingenuousness and spin to support its passage to universal applicability, is a massive contradiction, a disservice to professionals, and an artless deception worthy of our criticism and condemnation. Continue reading →

Big Data is Bullshit

11 Wednesday Nov 2015

Posted by in All Data, Big Data, Data Lake, Inform, educate and entertain., Martyn Jones

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“I’ve been accused of vulgarity. I say that’s bullshit.” – Mel Brooks

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

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Being brutally honest, Big Data is bullshit. Not only is Big Data bullshit but it comes with a surfeit of pranksters, pundits and prissy big data bullshit-babblers, all willing (cue narration by Morgan Freeman) to “big-up Big Data in a vulgar, ill-mannered and predictably nauseating dance of professional-hustling… as old as time.”

However, is all Big Data bullshit? Is it all a fad, a load of old tripe and a confusion of weasels together with their surfeit of weasel words? Or, is there something of value, substance and tangibility to be found amongst the volumes, velocities and varieties of brazen and opportunistic self-aggrandizement, toxic speculation and opinions and unverifiable miracles?

For Google, Facebook and Twitter, Big Data certainly isn’t BS. For example, Google rely on Big Data as the biggest irreplaceable element in their colossal advertising business – so I am lead to believe. A business that accounts for more than 90% of Google’s revenue. So clearly, for the masters of web-based unstructured and complex search, Big Data is an essential element in their business model. The biggest essential element by far.

However, let´s be honest, we should consider the obvious. How many of us are really going to do business like Google?

Big Data technology and service vendors benefit tangibly from the Big Data movement, at least this is the impression that I get. Indeed, there is much talk about the relationship between Big Data, the Hadoop ecosphere and the big wild world of open source, but what is more interesting is that companies are bringing in revenue on the back of Big Data by offering battle-hardened business and enterprise versions of open source software. Then there is the business in consulting, with such a demand for Big Data gurus, Master Data Scientists and Number Conjurors, there must presumably be real people working in these roles, and paid handsomely for doing so.

But apart from the ‘success’ associated with the foundation of so many Big Data start-up businesses and the market-based commitment of some of ITs’ ‘great and good’ to the new digital zeitgeist of data volumes, velocities and varieties, just where are the other success stories of Big Data coming from?

To help us in our quest, I earlier compiled a not-so-exhaustive list of Big Data success stories, celebrity-chef like, to help us out. Here are some of the Big Data gems that I managed to track down:

  • Thanks to Big Data, the taxi service alternative channel Uber is making massive waves and shaking things up in the transport sector.
  • By leveraging Big Data AirBnB is turning the hospitality business on its head, and what´s more, making friends, and influencing people as they are doing so.
  • Amazon would not be what they are today if it were not for Big Data, in fact, without Big Data, they would be nothing.
  • One of the industries that will suffer revolutionary transformation because of Big Data will be the banking industry.
  • Big Data will increase the GDP of the USA by at least 1% or more, and the Spanish GDP could likewise add an additional 1%, for similar reasons.

These would be all great headlines for Big Data success stories, apart from one small flaw. None of them is exactly a Big Data success story in the Big Data defining characteristics of volumes, varieties and velocities of mainly unstructured data or in terms of the Hadoop technological kitchen-drawer ecosphere.

Something is happening, and it is not exactly legitimate. Can you guess what it is yet?

When it rains it pours, and when it rains Big Data hype it quickly turn into a monsoon of cloying hysteria. Spotting and pointing at Big Data bullshit babblers on forums like LinkedIn Pulse, Forbes and Information Management is no fun, unless your fun is nuking a school of intellectually challenged fish floundering in a barrel of vintage Malmsey.

However, it not only is no fun, but also more times than not it is a complete and utter waste of time trying to get people to adopt a more critical approach to thinking. Because for every Big Data bullshit babbler, there is a battalion of intransigent Big Data believers stuck in untenable and absurd positions, marooned from reason and ways back to rationality. You can’t use logic against belief, and you can´t turn back a rising tide of IT refugees who are desperately seeking succour in the apparently safer-havens of Big Data, Data Science and Data-driven voodoo.

Only the other day I read that “The emergence of Big Data is now allowing CEOs to increasingly base decisions on current “reality” rather than past experience, but the risks in the integrity and fullness of the data that they are “seeing” and “hearing” is often a barrier to getting a clear picture of what is actually going on.” This is really taking shameless baloney and wilful ignorance to all new heights, but it doesn’t stop there.

Elsewhere another eminent Big Data bullshit babbler wrote, “Clearly big data and AI will change almost every industry this decade… but none more than these”, referring vaguely and vacuously to “Healthcare, Finance and Insurance”.  What species of shameless and fatuous willy-waving goes so far out on a limb that it becomes massively removed from even being a grandiose and beguiling ‘bigging-up’ of a fad?

Finally yet importantly, I almost choked on my supersized Big Data popcorn the other day when I read, “Today, with the rise of the Internet, we capture “data” on everything.  Therefore, the new term “Big Data” is honestly like 1985 again.  But this time, Big Data will actually be really big and by some forecasts, be a $40 billion industry by 2018.”

This is not hype, it is not even simple deceit, it is astroturfing of 22 carat bullshit, and in most cases it’s clearly deliberate, it´s intentional and it´s grossly misleading. So why do people do it?

Given that Big Data is very much a niche technology, with very much a niche appeal, why do so many buffoons go around pretending that Big Data is for all of us? Like as if it was some sort of digital universal-panacea, when at the moment, and at best, it is a walk on bit-player with just a couple of lies who aspires to B actor status. In this sense, at present Big Data isn´t even the hero´s best friend.

Before I close the piece, I will leave you with the thoughts of Dan Ariely. Why? Because it just irritates the hell out of a section of the community of Big Data bullshit babblers, and it´s actually very accurate. Here it is:

“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.

In subsequent blog pieces I will be sharing my views on the evolution of information management in general, and the incorporation novel and innovative techniques, technologies and methods into well architected mainstream information supply frameworks, for primarily strategic and tactical objectives.

As always, please reach out and 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 you will even consider sending me a LinkedIn invite if you feel our data interests coincide. Also feel free to connect via Twitter, Facebook and the Cambriano Energy website.

For more on this and other topics, check out some of my other posts:

Looking for your most valuable data? Follow the money – http://www.itworld.com/article/2982352/big-data/looking-for-your-most-valuable-data-follow-the-money.html

Stuff a great data architect should know –http://goodstrat.com/2015/08/16/stuff-a-great-data-architect-should-know-how-to-be-a-professional-expert

Big Data, the promised land where ‘smart’ is the new doh!–https://www.linkedin.com/pulse/big-data-promised-land-where-smart-new-doh-martyn-jones?trk=prof-post

Absolutely Fabulous Big Data Roles –https://www.linkedin.com/pulse/absolutely-fabulous-big-data-roles-martyn-jones?trk=prof-post

Not banking on Big Data? – https://www.linkedin.com/pulse/banking-big-data-martyn-jones?trk=prof-post

10 amazing reasons to join The Big Data Contrarians –https://www.linkedin.com/pulse/10-amazing-reasons-join-big-data-contrarians-martyn-jones?trk=prof-post

Amazing Data Warehousing with Hadoop and Big Data–https://www.linkedin.com/pulse/cloudera-kimball-dw-building-disinformation-factory-martyn-jones?trk=prof-post

The Big Data Contrarians: The Agora for Big Data dialogue–https://www.linkedin.com/pulse/big-data-contrarians-agora-dialogue-martyn-jones?trk=mp-reader-card

The Big Data Shell Game – https://www.linkedin.com/pulse/big-data-shell-game-martyn-jones?trk=mp-reader-card

Aligning Data Warehousing and Big Data –https://www.linkedin.com/pulse/aligning-data-warehousing-big-martyn-jones?trk=mp-reader-card

Big Data Luddites – https://www.linkedin.com/pulse/big-data-luddites-martyn-jones?trk=mp-reader-card

Data Warehousing Explained to Big Data Friends –https://www.linkedin.com/pulse/data-warehousing-explained-big-friends-martyn-jones?trk=mp-reader-card

Big Data, a promised land where the Big Bucks grow –https://www.linkedin.com/pulse/big-data-promised-land-where-bucks-grow-martyn-jones-6023459994031177728?trk=mp-reader-card

The Big Data Contrarians – https://www.linkedin.com/pulse/big-data-contrarians-martyn-jones?trk=mp-reader-card

Is big data really for you? Things to consider before diving in–https://www.linkedin.com/pulse/big-data-really-you-things-consider-before-diving-martyn-jones?trk=mp-reader-card

Big Data Explained to My Grandchildren –https://www.linkedin.com/pulse/big-data-explained-my-grandchildren-martyn-jones?trk=mp-reader-card

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, Martyn.

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.

Big Data, ESP and Transubstantiation

19 Wednesday Aug 2015

Posted by in Big Data, good start, goodstart, goodstrat

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vocationIf 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.

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. Continue reading →

Consider this: Big Data Luddites

21 Tuesday Jul 2015

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

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Bore da, pobl dda. A hyfryd dydd ‘Big Data’* i bawb.

When it comes to Big Data, some people accuse me of being akin to a Luddite. Nothing could be further from the truth. Not that the facts matter. In the age of superficiality and surfaces there is as much wilfully cultivated obliviousness as there is unashamed and unabashed term abuse. Add the prevailing underlying current of anti-intellectualism into the mix, and we have an explosive combination that manifests itself in the alliterative combination of bluff, bluster and banality.

— JOIN THE BIG DATA CONTRARIANS: http://www.linkedin.com/grp/home?gid=8338976

I was reticent about writing this article, because it’s a bit like arguing against the irrational, self-interested and wilfully obtuse. Or as Ben Goldacre would have it, “You cannot reason people out of a position that they did not reason themselves into.” Therefore, a lot of care needed to be exercised. Indeed, Mark Twain once stated, “Never argue with stupid people, they will drag you down to their level and then beat you with experience.” Now, I wouldn’t go that far, and I do try to be nicely diplomatic, most of the time, but I can see where he was coming from.

Anyway, without more ado let’s get a handle on what a Luddite is, in terms I hope that most will understand.

According to Wikipedia (yes, I know) The Luddites were:

“19th-century English textile workers who protested against newly developed labour-economizing technologies from 1811 to 1816. The stocking frames, spinning frames and power looms introduced during the Industrial Revolution threatened to replace the artisans with less-skilled, low-wage labourers, leaving them without work.”

So why do I get a feeling that some people think that I am a Big Data Luddite?

Here is Peter Powell of PDP Consulting Pty Ltd putting me in my place below the line on my piece titled 7 Amazing Big Data Myths:

“With all due respect – your post does sound a little like what I could envisage an exchange between a man riding a horse and a man driving one if the first automobiles….sorry.”

Although a respectable knowledge of the technology and its evolution would inform otherwise, I assume that this means that I would be the “man riding a horse”…  An interesting piece of conjecture indeed, even if hat in lacks in accuracy is made up for by the inexplicable certainty of belief. Still, it’s fascinating to discover just how many ‘experts’ think that this stuff – the sort of stuff I was doing in the mid to late eighties at Sperry and later Unisys – is bleeding edge innovation,

Sassoon Kosian a Sr. Director of Data Science at AIG, had this to tell me on my piece entitled Amazing Big Data Success Stories:

“Yes, cynical indeed… here is another amazing Big Data success story. You go on your computer, type in any search phrase and get instantaneous and highly relevant results. It is so amazing that a word has been coined. Guess what that is…”

What to say? There goes a person who seems to believe that the history of search starts and ends with the Google web search engine. Something slightly less than a munificently inapposite comment, only outdone by its tragically disconnected banality.

More recently, Bernice Blaar had this to say about my take on Big Data in general and The Big Data Contrarians in particular.

“Master Jones may well be the great and ethical strategy data architecture and management guru that the chattering-class Guardian-reading wine-sipping luvvies drool over, but he is also a brazen Big Data Luddite. No, actually far worse than a Luddite, he`s a Neddite, because with his ‘facts’ and ‘logic’ (what a laugh, you can prove anything with facts, can’t you [tou}???) he is undermining the very foundation of the Big Data work, shirk and skive ethic that has been so hardily fought for by the likes of self-sacrificing champions and evangelists of the Big Data revolution, to wit, such as those bold, proud and fine upstanding members Bernard Marr, Martin Fowler and Tom Davenport, for example, and the brave sycophants that worship at their feet. Martyn is worse than Bob Hoffman, Dave Trott, Jeremy Hardy, Mark Steel, Tab C Nesbitt and Bill Inmon, all rolled into one. He may be a great strategist, but I wouldn’t hire him. Contrarian Luddite!”

And then followed it up with this broadside:

“The Big Data Contrarians group are nothing more than a bunch of over-educated clown-shoes who are trying to scupper the hard-work of decent people out to earn a crust from leveraging the promise of a bright future. In a decent society of capital and consumers, they would be banned off the face of the internets.”

How does one reciprocate such flattering flatulence? How can one possible respond to such a long concatenation of meaningless clichés? Though to be fair, I quite liked being referred to as a Neddite, whatever that is.

Anyway, to set the record straight, this is where I stand.

A contrarian is a person who takes up a contrary position, especially a position that is opposed to that of the majority, regardless of how unpopular it may be.

Like others, I am a Big Data Contrarian, not because I am contrary to the effective use of large volumes, varieties and velocities of data, but because I am contrary to the vast quantities of hype, disinformation and biased mendaciousness surrounding aspects of Big Data and some of the attendant technologies and service providers that go with the terrain. I don’t mind people guilding the lily (to use an English aphorism for exaggeration), but I do draw the line at straight out deception., which could lead to unintended consequences, such as creating false expectations, diverting scarce resources to wasteful projects or doing people out of a livelihood. That’s just not tight.

Does that make me a Luddite (or a Neddite)? I don’t think so, but do make sure that your opinion is your own and is arrived at through reason, not some other persons bullying hype. As I wrote elsewhere some moments ago “If you have to lie like an ethically challenged weasel to sell Big Data then clearly there is something amiss.”

As always I would love to hear your opinions and comments on this subject and others, and also please feel free to reach out and connect, so we can keep the conversation going, here on LinkedIn or elsewhere (such as Twitter).

Many thanks for reading.

 

— JOIN THE BIG DATA CONTRARIANS: http://www.linkedin.com/grp/home?gid=8338976

Photograph: Delegates at my Big Data Summer Camp in Carmarthen (Wales).

*Data mawr

Raise the Big Data Flim-Flam High

30 Tuesday Jun 2015

Posted by in Big Data, Consider this

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If there were ever a more apt rallying slogan for the Big Data BS babblers it would be “We BS about Big Data so that you don’t need to think”… and you know what? That’s how it is working.

The trouble with the hype is that almost everyone and their dog is in on it. From the freelance or indentured Big Data gurus to the Gartners, IBMs and HPs of this world. Everyone who is anyone is trying to jump on the Big Data bandwagon, whether it makes sense or not. Hell, if I could become ludicrously rich and infamous on the back of Big Data, I would jump the Big Data shark as well.

The other trouble is that the Big Data hype is very inconsistent in almost all areas, apart from the general unstated agreement there seems to be that Big Data will bring riches beyond the dreams of avarice, for everyone who wants it.

So, let’s assuming that one wants to cash in on Big Data, what’s the first thing that we need to understand?

Big Data comes in big data volumes, it has many data varieties, meaning it has a number of distinct formats, and it comes at us with increasing velocity, which most of the time we simply do not notice.

So what does that tell us? Right, Big Data is data; just more of it, more flavours of it, generated and transmitted at faster and faster rates.  To simplify, data is like water (Oh, no not another analogy) and whereas Data Warehousing is the Rhine or the Mississippi Delta, Big Data is the Ma and Pa of the Iguazu, Victoria and Niagara Falls.

So, what were the next questions I asked myself on the way to the land of Big Data health, wealth and happiness?

I asked, “if you have a Big Data success story then let’s hear the skinny”, such as:

  • Please detail data that has used to create new insight and understanding?
  • How was this data sourced, treated and stored?
  • How was the resulting data queried? Let’s see the queries, the code, the pseudo-code and the code narrative.
  • What were the results of the queries? In technical and business terms, please.
  • What normalisation of the results took place?
  • How did those results drive insight? In business terms, please.

Perfectly straightforward, right? These are the sorts of questions that one should be able to ask of a Data Warehouse user and then reasonable expect to get a coherent set of answer back in return.

Well, seems like when it comes to Big Data this sort of line of questioning and reasoning is somewhat problematic.

Which is a problem, because I am seeing fantastic claims made for Big Data, which is great, and I wish we all could become more prosperous from Big Data, but I can’t seem to get a handle on quite how one goes about it. It’s as if ‘tangible’ was anathema when it comes to practical and detailed examples of Big Data in action. You know, driving tangible business benefits through an understandable value chain of processes, ingredients and outcomes.

So, come on Big Data guys, gals and gurus, it’s time now to pony up, put up or shut up.