Post-truth, Fake-news and Big Data

Martyn Richard Jones

Lora del Rio, 2nd February 2017


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

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

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

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

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

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Data Supply Framework 3.0 – ETL Patterns

Martyn Richard Jones

Mountain View, 22nd January 2015

image3This article is the first in a series of articles that discuss aspects of the use of architectural patterns in the Cambriano Information Supply Framework 3.0

The term architectural pattern may sound grand, misleading or daunting, but it’s really quite a simple concept. It’s like writing a function in a programming language to log in to a database, check that the connection is alive and working and report back the success of the connection request. If that function can be reused either in the same application development, in the same IT shop or in IT in general (e.g. Java code to connect and test the connection to SQL Server) then it’s well on its way to becoming an architectural pattern. Of course, there are much more sophisticated architectural patterns. But generally a pattern is a simplified and generic template for address a generally occurring problem. But as with much in architecture, less usually turns out to be more.

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Big Data is Bullshit – 2017

Marty Richard Jones

Mountain View, 19th January 2017

“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. Continue reading

Why I Really Like LinkedIn

It’s not something I have thought about a lot. But, apropos of nothing, a question came to mind. That question, as if you couldn’t guess by now, was “why do I like LinkedIn?”

Well, here is my first attempt at addressing this question.

I really like LinkedIn because:


Sunny, Guadalajara

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What Every CEO Needs to Know About Big Data

Martyn Richard Jones

New York City, 18th January 2017


Blue sky for professional data architecture and management


I’ll make this short, sweetish and to the point.

These are the arguments that CEOs need to know about Big Data.

It was written for CEOs and those who provide independent advice to CEOs.

If you are someone who wants to be prepared for CEOs who are armed with the realities of Big Data, then maybe this is for you too. Continue reading

Big Data Predictions for 2017

Mount_Everest_as_seen_from_Drukair2_PLW_editBig Data Predictions for 2017


You want Big Data predictions for 2017?

You’ve got ’em!

These are my Big Data, Data Warehousing and Analytics extrapolations for 2017. They are based on extensive, exhaustive and enigmatic work carried out by top-notch researcher gurus at Cambriano Energy, between December 2015 and December 2016.

So, stick with us as we survey the landscape that will be Big Data in 2017. Continue reading

Data on the Edge of Time and Place

image12Big Data on the Edge

This is all about data governance, time-and-place utility and striving to do the right, things right, first time and every time.

First up. Having been responsible for R&D in this area in the eighties I can honestly say that Analytics ‘on the edge’ is nothing new. So this is leading edge, not bleeding edge.

That stated, the big ‘Big Data’ vendors are finally catching up with the concept of data processing ‘on the edge’, a late adoption which has been accompanied by a flurry of fluffy and content-averse articles hailing this “new” (actually it isn’t new at all) approach to Big Data, the Internet of Things and Analytics ‘On The Edge’.

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BREXIT: Where’s Theresa May’s Plan B?

image12Martyn Richard Jones

Dublin, 10th September 2016

Theresa May, as Prime Minister of Her Majesty’s Government, has overall responsibility for organising the United Kingdom’s retreat from the European Union.

But, Theresa May has a problem, she doesn’t appear to have a detailed plan for Brexit, at all.

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UK POLITICS: The Jeremy and Owen Show

image10Martyn Richard Jones

Mountain View, Friday 9th September 2016

Although I am not a Labour voter, I, like many people across the UK, have been following the Labour Party leadership debates, which have seen the incumbent Labour leader Jeremy Corbyn and Labour MP Owen Smith battling it out in public. And although it’s not up there with Itchy and Scratchy, it still provides some surprisingly irritating entertainment interspersed with facts, fiction, Pontypandy bitchiness and Islington exasperation.

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BREXIT: Theresa May’s Catch-22

image7Martyn Richard Jones

Bamberg, 8th September 2016

Months have passed since the United Kingdom held its European Union membership referendum which resulted in a ‘win’ for the pro-leave Brexiteers. Yet the strongest signal coming out of London is that the government is stalling; playing for time. Clearly, as yet, the government hasn’t worked out in any real, concrete or detailed terms what it should be doing or where the country should be going or what it can even say to the array of stakeholders and interested parties. Which, given that Brexit is by far the biggest constitutional challenge in my lifetime, is quite problematic.

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