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Monthly Archives: January 2017

Data Supply Framework 3.0 – ETL Patterns

26 Thursday Jan 2017

Posted by Martyn Rhisiart Jones in All Data, Big Data, Big Data 7s, Big Data Analytics, business strategy, dark data, data architecture, Data governance, Data Lake, Data Supply Framework, Extract, Good Strategy, goodstart, governance, Inform, educate and entertain., Information Management, Information Supply Frameowrk, Information Supply Framework, IT strategy, Strategy, The Big Data Contrarians

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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.

Continue reading →

Big Data is Bullshit – 2017

19 Thursday Jan 2017

Posted by Martyn Rhisiart Jones in All Data, Big Data, Big Data 7s, Big Data Analytics, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, disinformation, governance, Inform, educate and entertain., information, Information Management, Information Supply Frameowrk, Information Supply Framework, pig data, The Amazing Big Data Challenge, The Big Data Contrarians

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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 →

CEO BRIEFING: What Every CEO Needs to Know About Big Data

18 Wednesday Jan 2017

Posted by Martyn Rhisiart Jones in All Data, Big Data, Big Data 7s, Big Data Analytics, business, Business Intelligence, business strategy, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Inform, educate and entertain., pig data, The Amazing Big Data Challenge, The Big Data Contrarians

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Martyn Richard Jones

New York City, 18th January 2017

OLYMPUS DIGITAL CAMERA

Blue sky for professional data architecture and management

Scope

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

01 Sunday Jan 2017

Posted by Martyn Rhisiart Jones in agile, All Data, Big Data, Big Data 7s, Big Data Analytics, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Inform, educate and entertain., pig data, The Amazing Big Data Challenge, The Big Data Contrarians

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Tags

1, 10, 2, 3, 4, 5, 6, 7, 8, 9

Mount_Everest_as_seen_from_Drukair2_PLW_editBig Data Predictions for 2017

Prologue

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 →

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