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Category Archives: Data Lake

Consider this: Big Data Inertia

22 Tuesday Mar 2016

Posted by Martyn 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, Inform, educate and entertain., pig data, The Amazing Big Data Challenge, The Big Data Contrarians

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“Half the time she did things not simply, not for themselves; but to make people think this or that; perfect idiocy she knew for no one was ever for a second taken in.”  Virginia Woolf, Mrs. Dalloway

It’s all very well for the blithering Big Data bullshitter savants to now claim, after a massive exercise in u-turning, that Big Data isn’t after all about data volumes, velocities and varieties, but about some minor variation on the theme of data architecture, management and processing.

But, look at the mess! Continue reading →

Too Much Information

16 Wednesday Mar 2016

Posted by Martyn Jones in All Data, Ask Martyn, Big Data, Big Data 7s, Big Data Analytics, business strategy, dark data, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Good Strat, Good Strategy, goodstrat, Inform, educate and entertain., IT strategy, Marty does, Martyn does, Martyn Jones, Martyn Richard Jones, pig data, Strategy, The Amazing Big Data Challenge, The Big Data Contrarians

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Martyn Richard Jones

I have questions about data.

Most of us who have more than a cursory knowledge of the English language have heard of the phrase ‘too much information’. We know what it means, even if we don’t always know when to apply it.

For those who don’t know, or are unsure, the Urban Dictionary describes ‘too much information’ as “An expression of exasperation and disgust when a person is divulging personal details of his sex life, toilet habits, or anything the listener finds disgusting, uninteresting, and unwelcome.”[1]

Sum, sum. Just because we know it, doesn’t mean we should share it or even try and remember it, never mind go about analysing the hell out of it.

This is where Big Data comes in. Continue reading →

Free Business Analytics Content –Thanks to Wikipedia – Part 4

09 Wednesday Mar 2016

Posted by Martyn Jones in All Data, Analytics, Ask Martyn, Big Data, Big Data 7s, Big Data Analytics, business strategy, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Good Strat, Good Strategy, goodstrat, Inform, educate and entertain., IT strategy, Marty does, Martyn does, Martyn Jones, Martyn Richard Jones, pig data, statistics, Strategy, The Amazing Big Data Challenge, The Big Data Contrarians

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Image1

Why buy when you can get it for free?

Back at you! Here is the fourth fantastic delivery of an amazing, fabulous selection of free, widely available business analytics learning content, prepared… just for you. Continue reading →

Free Business Analytics Content –Thanks to Wikipedia – Part 3

08 Tuesday Mar 2016

Posted by Martyn Jones in All Data, Analytics, Ask Martyn, Big Data, Big Data 7s, Big Data Analytics, business strategy, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Good Strategy, Inform, educate and entertain., IT strategy, Marty does, Martyn does, Martyn Jones, Martyn Richard Jones, pig data, Process, Strategy, The Amazing Big Data Challenge, The Big Data Contrarians

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Image4Why buy when you can get it for free?

Back at you! Here is the third fantastic delivery of an amazing and fabulous selection of free and widely available business analytics learning content, which has been prepared… just for you. Continue reading →

Free Business Analytics Content –Thanks to Wikipedia – Part 2

07 Monday Mar 2016

Posted by Martyn Jones in All Data, Analytics, 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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Image3Why buy when you can get it for free?

Back at you! Here is the second fantastic delivery of an amazing and fabulous selection of free and widely available business analytics learning content, which has been prepared… just for you. Continue reading →

Free Business Analytics Content –Thanks to Wikipedia – Part 1

05 Saturday Mar 2016

Posted by Martyn Jones in All Data, Analytics, 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, statistics, The Amazing Big Data Challenge, The Big Data Contrarians

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Image2Why buy when you can get it for free?

Here is the first fantastic delivery of an amazing and fabulous selection of free and widely available business analytics learning content, which has been prepared… just for you. Continue reading →

Testing the Data Warehouse

05 Saturday Mar 2016

Posted by Martyn Jones in All Data, Ask Martyn, Big Data, Big Data 7s, Big Data Analytics, business strategy, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Good Strat, Good Strategy, goodstrat, Inform, educate and entertain., IT strategy, Martyn does, Martyn Jones, Martyn Richard Jones, pig data, Strategy, The Amazing Big Data Challenge, The Big Data Contrarians

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Image1Martyn Richard Jones

Dusseldorf, August 2006

Data Warehousing provides possibly one of the best opportunities for IT organizations to deliver a valuable business solution in order to address a set of business needs; requirements that go well beyond the area of day to day operational support, and traditional applications (web enabled or not), and when Data Warehousing is done the right way, and for the right reasons, its payback to all of its stakeholders can be positively significant. Continue reading →

How Hadoop Revolutionised IT

05 Saturday Mar 2016

Posted by Martyn Jones in All Data, Ask Martyn, 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, hadoop, Inform, educate and entertain., Marty does, Martyn does, Martyn Jones, Martyn Richard Jones, pig data, The Amazing Big Data Challenge, The Big Data Contrarians

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This is the story of how the amazing Hadoop ecosphere revolutionised IT. If you enjoy it, then consider joining The Big Data Contrarians.

Before the advent of Hadoop and its ecosphere, IT was a desperate wasteland of failed opportunities, archaic technology and broken promises.

In the dark Cambrian days of bits, mercury delay lines and ferrite cores, we knew nothing about digital. The age of big iron did little to change matters, and vendors made enormous profits selling systems that nobody could use and even fewer people could understand. Continue reading →

In the Beginning was the Big Data Plan

23 Tuesday Feb 2016

Posted by Martyn Jones in Big Data, Big Data 7s, Big Data Analytics, Data governance, Data Lake, data science, Data Warehouse, Dogma, DW 3.0, Inform, educate and entertain., Information Management, Information Supply Frameowrk, Infotrends, Inmon, sentiment analysis

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Lucas_Cranach_d._Ä._035

In the beginning was the Big Iron, the Big Data, and the Big Data Plan.

And then came the Big Data Assumptions.

And the Big Data Assumptions were without form.

And the Big Data Plan was without substance.

And the Big Iron was without movement.

And the Big Data was without velocity, variety and volume.

And darkness was upon the face of the data workers.

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

And the data workers went unto their Data Supervisors and said: “This here Big Data is a pile of putrid crappy keech”, for they were from Govan, and continued, “and none may abide the odour thereof”.

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

And the Information Managers went unto their Business Directors, saying: “This here Big Data doodoo is a vessel of fertilizer, and none may abide its strength.”

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

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

And the President looked upon the Big Iron, the Big Data and the Big Data Plan, and saw that they were good.

Many thanks for reading

Join The Big Data Contrarians

The Big Data Contrarians

Big Data, a promised land where the Big Bucks grow

11 Wednesday Nov 2015

Posted by Martyn Jones in Big Data, Data Lake, data science, Martyn Jones, Martyn Richard Jones

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Big Data, Martyn Jones


B

Consider this: Many people come up to me in the street, and, apropos of nothing, they ask me how they can make money from Big Data.

Normally I would send such people to see a specialist – no, not a guru, but a sort of health specialist, but because this has happened to me so many times now, I eventually decided to put pen to paper, push the envelope, open up the kimono, and to record my advice for posterity and the great grandchildren.

So, here are my top seven tips for cashing in quick on the new big thing on the block.

1 – A business opportunity for faith

Like every new religion, trend or fad, Big Data has its own founding myths, theology and liturgy, and there is money to be made in it; loadsa lovely jubbly money. By predicating and evangelising Big Data you will be welcomed with open arms into the Big Data faith, and will receive all the attendant benefits that will miraculously and mysteriously fall upon you and your devout friends. Go on, I dare you. Be a Big Data guru, a shepherd to a flock of sheep, and enjoy the wealth, health and happiness that most surely will come your way. You too can look cool in red Prada slippers, a flattering and flowing gown and matching accessories.

2 – Acquire it, multiply it, weigh it, mark it up and sell it on

Simply stated, this is about acquiring other people’s data, by sacred means or profane, marking it up and then selling it on. The value you add is that you act as a trusted conduit, a conduit for good. You may care to enrich the data, swop the order of data, replicate and embellish data, make stuff up, etc. which all serves to ‘add value’ to the data. You may even consider adding nuggets of value to the data, just for kicks and giggles. My best friend’s favourite is injecting the good old ‘diaper and beer’ and ‘friends and family’ clichés into every Big Data collection, as it never fails to thrill, please and delight.

3 – Anything can be anything

The good thing about making money from Big Data is that it doesn’t need to be anything to do with Big Data. Make a 20GB Enterprise Data Warehouse? Call it a Big Data success. Sell 20 boxes of dodgy doughnuts down the alternative market? Proclaim a Big Data triumph. Sell your digital porn stash to your best mate? Point to the incredible invisible hand of the Big Data market at work. See what I’m doing there. Anything can be anything, and you too can cash in on that opportunity, big time.

4 – Big Data Patronage

Tense, nervous headaches? Do you like making up stories about Big Data, or for that matter anything else? Are you a natural born fibber but are strapped for cash? Then worry no longer. If you get a Big Data patron you will be sorted for ‘life’; get two and you’ll be sorted for the afterlife as well. With a Big Data patron you can get the most tenuous, crappiest and superficial of pieces published, promoted and vaunted – globally. Can’t make it up yourself, then outsource and offshore it, after all, just get the keywords right for SEO ranking and the gullible will flock to you in droves. The down side of this profession is that you will be targeted for writing half-truths, quarter-truths and downright lies, and you will be pilloried as a purveyor of rank hyperbole. But don’t worry, take heart and never lose the faith, you will be in good company. As one Big Data guru was want to say ” If you repeat a lie often enough, people will believe it, and you will even come to believe it yourself.” Amen! brother.

5 – Big Data Certification

By 2016 there will be global demand for 30 billion Big Data professionals. Are you prepared to cash in on that inevitability? No? Then consider this.

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 and a life in the city. Moreover, for an extra 250 bucks you can also become a certified Big Data Trainer, which will allow you to do unto others what has been done unto you.

6 – Creative Technology Reuse

Big Data has heralded in the biggest innovations known in the history of computing, and arguably in the entire history of humankind. One of those new inventions has been the now widely acclaimed and revolutionary ‘flat file data base’ (FFDB), and this has been accompanied with developments in low level operating system primitives that allow for the processing of these collections and hierarchies of FFDBs. So, if one has a mind to do so, one can get some real business leverage off of these new tendencies by borrowing 21st century technology found in old operating system hacks from the sixties and seventies and eighties and nineties and… Well, the point is that in order to get serious funding it is no longer good enough to have a half page business plan, it is also necessary to eke out ‘stuff’ that works within the new paradigms of Big Data and Big Data Analytics. For my next venture I will be looking for serious funding for my ‘Arbitrary Dawdle Down Data Street’ (AD3S) Big Data Analytics platform, a platform designed to support virtual 1k bit processing and the massively parallel provision of global regular expression search and match (S&M), concatenation and listing, and cooperative data-driven and streamed data extraction and reporting. I’m hoping to attract the attention of governments, the EU, the Manic Street Preachers, the UN, China, Vladimir Putin, the DOD, HP, Oracle, Gartner, Lana Del Rey, Deloitte and IBM. So, this is going to be absolutely massive. Word!

7 – Big Data Brokerage

According to leading management consultants and industry watchers Gartner, McKinsey and Deloitte, data needs to be managed and accounted like any other asset, such as money. To get into a similar view-point requires a massive leap of faith, but it is a conversion that might drive dividends. One avenue to be explored in eking out value from the apparently massively valuable Big Data lakes, silos and pools is through the operation of a Big Data Brokerage. A Big Data Brokerage is a business whose main responsibility is to be an intermediary that puts Big Data buyers and Big Data sellers together in order to facilitate a transaction. Big Data Brokerage companies are compensated via commission after the Big Data transaction has been successfully completed. They may also charge introductory fees. Just imagine the wealth of business opportunities in that. You could become the Goldman Sachs of data.

That’s it folks!

I hope you enjoyed this piece and would be pleased to hear your views on this and other subjects.

Whilst I understand the attraction and even the need of creating a new and significant growth industry, I would also advise a degree of restraint, and whilst I see that “Big Data” (the consideration of the potential value of All Data) has its allure, I also think that some good sense and informed caution should also prevail.

Thank you so much for reading.

Martyn Richard Jones

Spain, 2015

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