Raise the Big Data Flim-Flam High

30 Tue Jun 2015

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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.

The Amazing ROI of Big Data

30 Tue Jun 2015

Posted by in Big Data, Consider this, Strategy

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For every professional bubble-head and bozo ‘bigging up’ Big Data there are at least ten intangible, unintelligible and phantom Big Data success stories.

Why do I write that? Simples! Because that is what we have.

From the perspective of non-IT business users, what does a real IT based success story look like?

Here’s some examples:

  • We ran a Big Data project and the end-result was increased sales and margins, which added $21M to the bottom line. The overall project cost, including cost of business disruption, was $7M.
  • We deployed Hadoop technology to identify potential influencers and purchasers on Twitter. As a result of the campaign we increased sales of the Widgets by 8% (adding $9M is revenues and $3M in profits on an investment of $1M).
  • Big Data helped us to identify and exclude significant errors of judgement introduced into our new corporate strategy. As a result we averted possible losses of more than $10M. Total cost of aversion exercise was $5M. $5M up and no egg on our faces.

These are fictitious examples of tangible benefits that might be accruable to Big Data. But, they are not factual, they are made up.

Remember this. They are not real-life stories.

Now, for some real-lifelike examples of benefits accrued from Big Data.

  • Big Data vendor strikes gold! The Big Data technology vendor GREPACLE today signed an enterprise wide licensing arrangement with the Fed for an estimated initial $750M, covering the years 2010 to 2017. The deal includes all industry-ready Hadoop “free ‘n’ open-source software” developed by GREPACLE. AWKACLE, who brokered the deal, expect to clear a $33M net profit from the arrangement.
  • OLLY-HARDY, the west coast hardware giant, has signed up WALLYCO who have handed over $60M as the first instalment for the provision of a cheap and cheerful battle-hardened commodity-hardware infrastructure that will replace the existing legacy infrastructure currently based on OLLY-HARDY MPP and SMP hardware and Oracle and Teradata software. A second contract billed to be worth in excess of $100M is in the pipe-line and is expected to be signed during the next quarter.
  • The profits of information theology research and technology advisory firm Gardening Leave jumped a clear 25% over the last three quarters due solely to sales of it’s reports and services in the Big Data domain.

The names changed, and the project details finessed, to protect the guilty, but they are three simple, clear and fabulous examples of how gold is obtained from Big Data.

However, there are many other Big Data success stories to consider, including:

  • The indentured Big Data pundits. Who wouldn’t lie for a slice of the pie? Right! But not everyone has scruples, values or even ethics when it comes to the filthy lucre.
  • The pro-Big Data press and their Big Data advertisers and ‘infomercialisers’. There still is money in getting people to advertise, big time.
  • The external service provider. The hardware may be commodity. The disk storage may be ample, cheap and cheerful. The unit cost of staff may be lower. But, you will be paying 10 times over the odds to your favourite outsourcer/offshoring business just for the privilege of having them screw up your Big Data project… 18 months down the line. You will even pick up the tab for breaches of data privacy and data protection. But don’t worry, paying someone else to make mistakes and learn on your money and time is the highest form of corporate altruism.

Well, that should give one a flavour of the direction of Big Data, of the benefits accruable and to whom the benefits really accrue.

Now here’s a thought:

Most of the success stories seem to have the sale of a Big Data project, Hadoop’s ‘grep awk ecosystem’ and ‘development’ services as its central tangible success criteria.

At best, these are dubious Big Data tech and service vendor success stories.

What tangible Big Data client benefits are there on view in the public domain? How about non-IT business Big Data ROI? Same for Hadoop ROI? Same for Big Data and Tech Stack service ROI?

What about… Who? What? Where? When? How? Why?

Oh, there aren’t any success stories like that or they are so secret that one cannot but allude to them in generic BS terms.

But, seriously? Do people still swallow that type of mendacious flim flam?

Many thanks for reading.

Big Data Explained to My Grandchildren

29 Mon Jun 2015

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Ban pan doeth peir

ogyrwen awen teir

The Book of Taliesin 

Once upon a time, a hobgoblin of digital moonshine stalked the land. Its name was Shirley Temple (but, it was better known as Big Data), and it had many followers.

Few really knew where Big Data had come from, because it just appeared overnight. Like owls, snow, rumour and astroturfing flim-flam merchants.

Some say the Gardner brought it in on the bottom of their wellies after a particularly tough night on the lemonade.

One night, a man with a black dog told me that it was really all a load of old nonsense, dreamed up by Redwood Shore Larry, to shake things up a bit.

Others, of the more superstitious bent, claimed that the giant who lived in the Big Blue mansion on the hill, had concocted it, from sugar and spice and all things dodgy and nice

The more cynical amongst the population just pointed at its high priests, acolytes and bicycle boys, and had a good old laugh.

Yet others claimed that it was a digital immaculate conception and a divine-revelation of mega-trend setting proportions that would change the face of the Lleyn peninsula, forever.

Elsewhere, some talked of dark deeds, of wickedness, or that it was a psycho-paranormal phenomenon closely associated with the cultish cult of the badly drawn Yellow Elephant. A wonderful wacky, off-the-wall and global orco-centric sect that sacrificed the processing-cycles of reason, strategy and coherence on the altar of half-baked pragmatism, bodgerism and winging-it.

Nonetheless, some of the global villagers did express opinion that this was no new phenomenon, and that they had seen such a sinister semblance before. Knowledge and experience had informed them. They seemed to intrinsically know that a timeless feature of data is its variable volumes, its variable velocities, its increasing varieties and, because we insisted on hoarding so much of it, its increasingly expansive footprint.

But, how did they know?

They only had the gardener, the butler and the cook to corroborate their suspicions.

We know what we know, and what we don’t know we know what we don’t know, now, that is, but don’t tell, unless we do, or don’t, or not. So I’m glad we cleared that one up.

Down the valleys, across the moors and over the waves. From Bangor to Abertawe via Machynlleth and Caerfilli. Big Data, it moved and expanded, and expanded and moved again. Dong! Dong! Dong! Ominous, humongous and smelling of sulphur and a badly spiced kebab.

The Big Data mini-meme spread like wildfire fuelled by petrol and crack. It was a force to be harnessed, a force for good and bad. Even though no one really knew what it was, and nobody knew how to do it, many claimed to have done it, and successfully so. It didn’t matter how, what where or when. Front interface, back-end processor, client-server, no one and nothing was free or safe.

The benevolent Big Data virus reached everyone. The rich, the poor, the shop on the corner, and the girl next door. Everyone knew its name and that it was new and mega and good and bad and all of that.

The thing is, Big Data wasn’t really anything new. As we now know.

But, at the time, for some people, especially the so called high-ups and professional people, it was a big deal, even in Pontypridd! Like a major inflection point in the evolution of the generation and use of what we now call data, or to use the vernacular, digital gold-gold.

You see, back then, people wanted to make another class of data and another class of gold, and another series of lovely, chubby little verbose categories to describe it. People needed another name, one that represented some data class values, spirituality and imprecision. It was a time of post-modernism, and we were always stoned, mazed or drunk.

Some of my peers at the time – not all of them, just the exceptionally plain Jane, weird and alternative ones – told me that Big Data was data that came in bigger volumes, at greater velocities and in greater varieties.

The first I heard that, I was gobsmacked… Honest to God!

I know probably you’ll laugh at that, now, and you may even tell your friends and butties just how superstitious, primitive and money-grubbing we were back then.

So whilst you are making fun of your old granddad, do not forget either, that is the way it was in those days, down the data mining towns and Big Data pits of South Wales.

I know it is hard to believe, but back in those days, people really believed in that nonsense. I didn’t have any time for it myself, but many did, and many people made a living of sorts just talking and writing about it.

It’s hard to believe now, but at one time we were really dumb, but as we didn’t want to stand out from the crowd by revealing that we didn’t know, we just stood back and let the buffoons, clowns and comics run the show. Whilst we exclaimed, “these guys are really good”, “I wonder if he can turn Big Data into wine” or “maybe he does requests and children’s parties”.

Now we look at data, all data, and we call it…. Yes… data.

How we have advanced. It’s amazing.

But then, when it all died down, as these things do, in their given time, we regained our senses, of sorts, we got back on our feet and we progressed in a sane, rational and humane way.

Now we can look back and see things for what they were. The Big Data hullaballoo, that you have never heard of, was the last gasp of some the biggest IT dinosaurs, who had tied their hopes and aspirations, ridiculously so in my view, to some toys created by the naïve for the gullible. It was always going to end in tears, and it did.

Now you know.

So, this ends the story of Big Data, also known as Shirley Temple.

Goodnight kids!

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.

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

#BigData #BigDataAnalytics #Decency #Ethics

Is big data really for you? Things to consider before diving in

13 Sat Jun 2015

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“For the likes of Google, Twitter and Facebook, Big Data is an intrinsic part of their business and plays a key role in their ability to survive and thrive. However, it is not for everyone. Here’s how to know for sure if Big Data is for you.”

The rest of the article appears on my IT Circus blog hosted by IT World (Copyright © 2015 IDG Enterprise)

Link: http://www.itworld.com/article/2934368/big-data/is-big-data-really-for-you-things-to-consider-before-diving-in.html

#BigData #DataAnalytics #Qualification

Let’s talk strat! Business Strategy and IT

22 Fri May 2015

Posted by in business strategy, Consider this, Good Strat, goodstrat, IT strategy, Strategy

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I used to work for an affable person from Chicago. His two favourite phrases were “Let’s talk strat” and “Brought your cheque book with you?”

There are many misconceptions about strategy. But, I particularly want to address two things:

  • What is business strategy?
  • What is IT (information technology) strategy?

So, without more ado, let’s get the baby off the ground.

Continue reading →

The Hadoop Honeymoon is Over

16 Sat May 2015

Posted by in Big Data, Consider this, Good Strat, Good Strategy, Martyn Richard Jones, Strategy

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Listen up Big Data playmates! The ubiquitous Big Data gurus, tied up in their regular chores of astroturfing mega-volumes, velocities and varieties of superficial flim flam, may not have noticed this, but, Hadoop is getting set up for one mighty fall – or a fast-tracked and vertiginous black run descent. Why do I say that? Well, let’s check the market. Continue reading →

On Not Knowing Sentiment Analysis

12 Tue May 2015

Posted by in Big Data, Big Data Analytics, Consider this, good start, goodstart, sentiment analysis

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If you know all about Sentiment Analysis, you’ve come to the right place. Because I don’t have a clue if what I know about it is accurate or not.

I started to do a bit research into this Sentiment Analysis lark, in particular with the theoretical idea of using it to analyse and draw conclusions from comments on Pulse – assuming that this is what it can be used for.

To begin at the beginning, which is good place to start, I read the piece on Wikipedia, and this was how it began:

“Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials.

Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. The attitude may be his or her judgment or evaluation (see appraisal theory), affective state (that is to say, the emotional state of the author when writing), or the intended emotional communication (that is to say, the emotional effect the author wishes to have on the reader).” Source: Wikipedia Link:http://en.wikipedia.org/wiki/Sentiment_analysis

Well, that’s a fairly intuitive description. I could have almost have guessed as much.

But, back to the aim of analysing sentiment in Pulse comments, where to start and what to do.

What would sentiment analysis make of these:

On the death of an IT-business celebrity. What would sentiment analysis make of the very emotive comments of desolation, sadness and poignancy of people who didn’t personally know the departed, even remotely, or maybe didn’t even know of them until after they had ‘shuffled off life’s mortal coil’? How would that work? What would sentiment analysis make of the maudlin aphorisms, surrogate grief and bizarre sorrow of people separated by more degrees than Kofi Anan and Mork from Ork.  What additional insight does sentiment analysis tell us when these comments are analysed along with the body of the text and other comments that triggers these comments?

In a similar vein, how does sentiment analysis catch instances of sycophancy? Especially considering the fact that some of it is so ‘in your face’ and blatant that it often times seems to be a bad parody of a bad parody. “Oh, Ricky, why are you such a sexy brainbox?” How does it work in those situations?

Worse than that is the preening, gushing and obtuse texts of massive, errm… fabulators[i]. If it wasn’t about Big Data or Strategy or IT, it would be about something else, usually about the writer themselves. “I give Rafa and Rodge tips on tennis! I went to the University of the Universe and got a first! I challenged Superman to a race, and won! I have read the entire works of Dan Brown, 25 times…Neeeh!” What would sentiment analysis do with that sort of gold?

Also, what does sentiment analysis do with texts so ambiguously daft that they could mean anything? Okay, it might be able to pick up a few trigger words here or there, “rubbish”, “of”, “load”, “a”, “what”, etc. However, how does it know when “excellent” is being used in a way that means anything but excellent? For example, “Excellent Big Data job there”, with the silent “if you want a job doing properly then do it yourself”.

Finally, for the purpose of this little piece, what would sentiment analysis do with term abuse, if it could actually identify it? Going back to the use of the terms such as Big Data or Strategy, how can sentiment analysis discern between the dopey and wrong-headed use of the term, and when it is actually being used in a coherent, cohesive and consistent way, in line more or less with its formal definition? I suppose we can always write a mountain of rules to help us out:

If topic in focus of piece is strategy

And context of topic is business

And author of piece is Richard Rumelt

Then the credibility of text is good (with a certainty of 100%)

But you and try and maintain a rule base with isntances like that. It soon becomes a management nightmare.

Alternatively, maybe it could be used to analyse this text. It’ll have its work cut out, that’s for sure. Does sentiment analysis do sarcasm and cynicsm?

Anyway! I bet you might know how this sentiment analysis works, don’t you? On the other hand, if not, then it will be someone else who ‘knows’. But of course, all will not be revealed, because it’s a secret so powerful, that in the wrong hands it could be used to dominate the entire galaxy.

Only joking; and many thanks for reading.

[i]To engage in the composition of fables or stories, especially those featuring a strong element of fantasy: “a land which … had given itself up to dreaming, to fabulating, to tale-telling” (Lawrence Durrell).

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Big Data Tales: Bernice and the Martians

12 Tue May 2015

Posted by in Big Data, Consider this, good start, goodstart, goostart, Martyn Jones, Stories

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Bernice and the Martians, BATM for short, were an incredibly popular progressive-rock band.

Their first big commercial success came with the release of their first album and their planned promotional tour, which took in all continents.

The manager of the band was none other than effable polymath, Renaissance man and good all-round rogue, Ricky Jonesy – an obsessive control freak, lover of fine wines and darling of predictive analytics. He really loved his numbers, his social media and his sentiment analysis.

In fact, much of the early success BATM came about due to Ricky’s unparalleled passion for the ‘Big Data’.

Ricky was the band’s architect. He had major input into their material: what they composed; how they composed; their stage sets and lighting; where they performed; the way they played; how they dressed; were photographed; spoke; walked; and, ate and drank. In short, he controlled the whole BATM enchilada. It was like being in data-driven heaven.

As I said, their first album, a progressive-rock masterpiece called ‘Your Hole’, achieved major critical acclaim even before it was bolting out of the stalls and across the interwebs. Overnight the band became big property, and their notional market value ran higher than Twitter on steroids.

The band members were really please. The presses interviewed Bernice right, left and centre and he made no bones about the fact that a major part of their success was due to Ricky and his Big Data mojo.

Articles about the phenomenon appeared in all the major social media sites. Facebook, LinkedIn and BubbaToons. Ricky was named Supreme Data Scientist of the year by the Gardener Group, hailed as a messiah by the Big Data Front and lauded by all and sundry.

Then the band went on tour. Blazing a trail of ones and zeros across the face of the planet.

They were 5 gigs into their tour and Ricky decided to call a band meeting.

“Hi, guys” said Ricky “I’ve been analysing the stats, and I see that those yokes Big Blokes in Tights are trending strongly on the social media, coinciding with the release of their new single Never Stick A Banger In Your Ear”.

“Oh, whoa” chimes in Bernice, “tell us what we gotta do then, Ricky”.

Back comes Ricky. “Well, this is what I thought we might do”

“We take the old Fester and Ailin song Tropical Diseases, we practice it as much as can, and then we play it at the next gig in Birmingham, this weekend”

“But, Ricky!” pipes up Marty Smarty, “it’s an Irish country and western song. It doesn’t fit in with what we do, does it? And, anyway, we only have three days to get it prepared.”

Ricky responds. “Ah, you don’t want to be worrying your little head over that. Trust me. Learn the song. It’ll be great. The public will love it.”

So, BATM learn the song. It’s perfect. At the Saturday gig, they play it as the encore. The fans love it to bits and there’s not a cold cigarette lighter in the place.

Then they fly off to Palma de Mallorca for a bit of a rest before their next gig in Madrid.

The guys and gals are lounging at the poolside at the legendary Don Pimpón Espinete Plaza complex. The weather is glorious, the food is glorious, the scenery is glorious, and even the orchestra is glorious.

Then along comes Ricky, calling yet another band meeting.

“Hi, guys” said Ricky “I’ve been analysing the stats again, and I see that those yokes Spanky’s Magic Piano are trending strongly on the social media with their cover version of Engel Humpadink’s The Monkey Song”

“Oh yeah, what’s that mean for us, Ricky” chimes in Halo Popette, the bands keyboardist.

Back comes Ricky. “Well, this is what I thought we might do”

“We take the old Fester and Ailin song There’s A Dead Man Up The Chimney, and we rewrite it in the style of Tom Jones when he made that album of his, Little Fockers, was it? Then we practice it as much as can, until it’s perfect, and then we play it at the next gig in Madrid, this weekend”

“But, Ricky!” pipes up Brian McGarsical, “It’s a bit of an odd one isn’t it? I mean to say, it doesn’t fit in with what we do, does it? And, anyway, we only have four days to get it prepared.”

Ricky responds as fast as a chalked-up cat going down a drainpipe. “Ah, you don’t want to be worrying your little head over that. Trust me. Learn the song. It’ll be great. The public will love it. And anyways, it will fit nicely on the playlist, up there with Tropical Diseases.”

The band rewrite the song, and practice the Bedejaysus out of it. Ricky likes it so much that he gets the stats to confirm that this has to be number one on the next gig playlist.

Come the day of the gig, and BATM kick off, not with a progressive-rock anthem, but with There’s A Dead Man Up The Chimney. A group of young people at the front clearly are loving this new sound, but quite a few people are starting at the stage in fright, and it’s not from skunk induced paranoia either.

Two guys are having a conversation at the back of the hall.

“Yo, lunchbox, hurry this gig up, I thought this band was all progressive-rock and stuff, not this wiener schnitzel stuff.”

“No comment.”

Having divided the crowd with their first song, they play songs from their album. Again, they encore with Tropical Diseases. The crowd at the front go wild. The progressive rockers look on, bemused.

“Well, that was a mixed bag” says Bernice.

“Take it from your man Ricky. It all went fine lads. Just needs some fine-tuning of the songs and the analytics need to be a bit more real time. Take me word for it.”

Back comes a unison of “Okay, Ricky. We believe yas!”

So, off they go to Bonn, to prepare for the following weeks gig at the Live Music Hall in Cologne.

The band goes out visiting the museums, they have lunch at Brauhaus Bonnsch, and after a leisurely walk along the banks of Rhine they are taking a beer or three in a lovely little beer garden close to the United Nations campus.

Then out of the blue, a familiar voice can be heard.

“Hi, guys! We’re all goin’ on a summer ‘oliday”. It’s the voice of Ricky. “Anyway, Good news guys. I’ve been analysing the amazin’ Big Data stats again, and I see that those mensch Die Zahnarzt are trending strongly on the social media, especially on Swotter and Titter, with their amazon’ cover version of Podge and Rodge’s chillout mix of Currywurst and Microchips.”

Silence. No one says a word for the best part of infinity.

Ricky continues… “As you’re not going to ask, lads, I’ll tell you. We take the old song A Great Day for the Washing, and we rewrite it in the style of techno-Buddah-bar-chill. Then we practice it as much as can, until it’s perfect, and then we bang it out at the next gig in Cologne, this Friday. Innit. Come on lads, it’s 20 minutes of stage magic, and it’s a breeze.”

Come the day of the gig, and the band arrive early at the hall. Ricky is already there. He’s changed the stage set completely and has a new wardrobe for the lads – Bavarian romantic. They’ll soon be all Princed and Smiley Virused up to the eyeballs, wrecking ball included.

and BATM kick off, not with a progressive-rock anthem or chill, but again with There’s A Dead Man Up The Chimney. Again, a group of young people at the front clearly are loving this new sound, but quite a few people are starting at the stage in drug induced awe. Then they follow that up with A Great Day for Washing. By the time they get to the encore of There’s A Dead Man Up The Chimney, boisterous arguments are breaking out everywhere and empty crisp packets and used sticks of chalk are being thrown at the stage. It’s a disaster.

Four guys are having a conversation at the back of the hall.

“I liked the first song”

“No! The first was terrible. Minging! I want my prog rock back.”

“It’s like the choice of leprosy or the plague.”

“Down with this sort of thing.”

Next day Bernice calls an urgent meeting of the band.

Ricky kicks off.

“Well, lads bit of mid-week game yesterday wasn’t it?”

Bernice comes back with a “You can say that again, Rick”

“Don’t worry, I have analysed the social-media Big Data from all of the concerts, and we’re doing good guys. It’s in the analytics”

“We have to go back to our roots and drop all the changes we made”

A stranger in the lounge where they are having the meeting walks up to them and in simple language explains to them what has happened.

“You created a great product, a great brand, with some interesting progressive music”

“Your music was acclaimed and your world tour was eagerly anticipated by all your fans”

“But then you went wrong”

“You became data driven, dopey and data driven”

“You chased fads, tendencies and styles, and it became a mish-mash”

“People don’t want mish-mashes. Not your base. They wanted good progressive music”

“You’ve lost all credibility. No, you’re just an eccentric band of brothers and sisters that no one will really want to see more than once, if at all”

“Your former fan base is acutely embarrassed by you. That’s your bread, butter, vodka and caviar… in your terms”

“Data drive, Big Data, Big Data analytics in real time?”

“You people have no idea the damage you can do, and so easily”

To be continued…

Many thanks for reading.

Consider this: Taming Big Data

01 Fri 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 →