• Home
  • About
  • The Good Strategy Blog
  • Strategy
    • Data Warehousing
    • Ask Martyn

GOOD STRATEGY

~ for every significant challenge

GOOD STRATEGY

Category Archives: good start

Consider this: The ten key dimensions of Applied Business Knowledge and AI

22 Thursday Jun 2017

Posted by Martyn Jones in 4th generation Data Warehousing, Artificial Intelligence, Ask Martyn, good start, Good Strat, Good Strategy, Good Strategy Radio, knowledge management, Marty does, Martyn does, Martyn Jones, Martyn Richard Jones

≈ Leave a comment

10 dimensions B

AI, KNOWLEDGE, INFORMATION AND DATA

“Knowledge is the capacity to give correct answers to questions.”

“There is no well trodden path that takes a straight line from symbols, through data to knowledge and wisdom. This is just some nonsense invented by the IT industry.” – Martyn Jones

We may define data as being the symbolic representation of value or conversely of something which has no attached value. Data may represent, among other things, time, money, resources or worldly objects.

Continue reading →

Seven Magnificent Big Data Success Stories

31 Wednesday Aug 2016

Posted by Martyn Jones in 4th generation Data Warehousing, All Data, Ask Martyn, Big Data, Big Data 7s, Big Data Analytics, Cambriano, dark data, data architecture, Data governance, Data Lake, data management, data science, Data Supply Framework, Data Warehouse, Data Warehousing, good start, Good Strat, Good Strategy, goodstart, goodstartegy, goodstrat, Martyn does, Martyn Jones, Martyn Richard Jones, pig data, The Amazing Big Data Challenge, The Big Data Contrarians

≈ Leave a comment

Mount_Everest_as_seen_from_Drukair2_PLW_editMartyn Richard Jones

Lora del Rio, 31st August 2016

Big data has arrived. Big Data is here for keeps. Big Data is the future.

Despite some of the malicious, mendacious and malodorous words of naysayers, sceptics and contrarians, the world of big data and big data analytics is replete with totally amazing and fabulous success stories.

Big Data gurus are often accused of not delivering coherent, cohesive and verifiable accounts of Big Data successes. Which is understandable but at the same time a pity. So here, to illustrate this miraculous and remarkable turnaround, I give you not three but seven of the many Big Data success stories that I could have casually grabbed out of the ether.

First, we take a trip to Glasgow to discover the leveraging of Big Data in alternative investments. Then we pass over to Boston to explore the magic of Big Data at Universal Legal. We venture through Switzerland and innovative marketing. Explore the heights of Dongalong Creek. Have a word with the good folks at Heisenberg Labs. Then round it off with a quick in-depth summary of Big Data at Choppers. So, here we go…

Continue reading →

Big Data on the Roof of the World

29 Monday Aug 2016

Posted by Martyn Jones in 4th generation Data Warehousing, All Data, Ask Martyn, Big Data, Big Data 7s, Big Data Analytics, business, Business Intelligence, business strategy, dark data, data architecture, Data governance, Data Lake, data management, good start, Good Strat, Good Strategy, goodstart, goodstartegy, goodstrat, Martyn does, Martyn Jones, Martyn Richard Jones

≈ Leave a comment

Mount_Everest_as_seen_from_Drukair2_PLW_editOnce upon a time, there was a mountain known as Peak 15. Very little was known about it. Then in 1852, surveyors found it was the highest in the world, and they named it Everest.

As with other significant challenges that we can identify in life, many people have been driven by a passionate desire to conquer peaks all around the world. This is just one illustration of those of us who can identify their significant challenges and rise to them. This sharp focus, determination and courage turns ordinary citizens into people who are invariably on a mission. People who know what they want. Continue reading →

The Digital Document Lifecycle

01 Tuesday Dec 2015

Posted by Martyn Jones in data architecture, Data governance, data management, ECM, good start, Good Strat, Good Strategy, governance, Management, Martyn Jones, Martyn Richard Jones, Uncategorized

≈ Leave a comment

Tags

Content Management, ECM, Good Strat, Martyn Jones, Strategy

The Digital Document Lifecycle

MARTYN RICHARD JONES

To begin at the beginning

This is a story of the life of a digital document. Its purpose is to explain the process of analysing, designing, building, testing and delivering content rich business artefacts in today’s digital age.

Continue reading →

Big Data, ESP and Transubstantiation

19 Wednesday Aug 2015

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

≈ Leave a comment

Tags

Big Data, Consider this, good start, goodstart, goodstrat, Martyn Jones

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 →

Why so many ‘fake’ Big Data Gurus?

16 Sunday Aug 2015

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

≈ Leave a comment

Tags

Big Data, cynicism, data management, fakes, good start, goodstart, gurus, Martyn Jones, Martyn Richard Jones, Strategy

Why so many ‘fake’ Big Data Gurus?

Where do you all come from?

Where do you all come from?

All your integrity’s gone

Now tell me, where do you all come from?

From ‘Where Do You All Come From‘ by Mott the Hoople Continue reading →

Big Data, the promised land where ‘smart’ is the new doh!

03 Monday Aug 2015

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

≈ Leave a comment

Tags

Big Data, Consider this, goodstart, Martyn Jones, Strategy

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.

So you want to ‘do’ Big Data

Now everyone is doing Big Data you don’t want to be the odd one out, right? Of course not.

Now, if you are serious about looking at Big Data from a business perspective then I will try and lend you some advice. If you are doing it from an IT or technology perspective, then I wish you good luck, and I hope that your Big Data initiative doesn’t turn into another tech crash-and-burn show.

Now some Big Data pros are telling us that the place to start with Big Data is with strategy. Now, I’m too polite to call this out as abject bullshit, even though it is, and will instead content myself by offering an alternative and simple approach to approaching and addressing Big Data.

My first piece of advice is this. DON’T START WITH STRATEGY!

Don’t start with Strategy

Strategy is a coherent, cohesive and executable response to a significant challenge.

Strategy is not a definition of objective, a wish list of what you are trying to achieve or aspirational goals of a nebulous nature. No, strategy is not the objective but a means of reaching that objective. Strategy is real, tangible and executable. Strategy is doing.

So what is a Big Data strategy?

If a company is looking at the Big Data options, the last place they should want to start out from is from strategy. That is as silly idea as they come. Starting with strategy on the road to formulating viable responses to significant challenges and opportunities is like saying that before we choose strategic options and a realisable strategy, then you must have a strategy in place.

Strategy is not working out what you want to achieve. That sort of thing should happen prior to any strategic work. Neither is strategy an exercise in establishing starting points, nor formulating questions nor understanding the challenges. All of this should come well before the major strategy aspects even kicks-in.

Big Data strategy is a realisable, tangible and manageable response to a significant challenge, one that depends heavily on the availability, usability and credibility of Big Data (or Very Large Data Bases) and the business value of processing that Big Data.

So, a word of advice. If you are thinking of embarking on a Big Data initiative, do not start with strategy. That is a really daft place to start.

Start with business imperatives

Start here instead. With real business imperatives. This is where you are thinking about the big and significant challenges to the business, and how, at a high level of abstraction, you could go about meeting those challenges. Here you identify your challenges and your responses, aligned to your objectives.

If you can identify business imperatives that make it absolutely necessary to include elements of Big Data, then go forward with that mandatory requirement in mind. If not, then don’t try to shoe-horn Big Data into a place where it really isn’t needed or wanted. Because if you go against the grain in this way it may well hurt you and your business, in more ways than you bargained for.

Know what you are looking for

In order to go out looking for data requirements driven by business imperatives, we really need to know what we are looking for.

What we are looking for maybe highly tangible or less so. We may have to derive the data we are looking for by refining, aggregating, enriching, filtering and cleansing. Therefore, with those and other aspects in mind, we can go out and find what we need.

How to find what you are looking for

From looking at the data requirements, you should have a good idea of potential sources of that data. Agility in this aspect is predicated on the premise that one knows the systems on the IT landscape, the business processes and all the potential sources of data – at a high level at least. So, this is not the sort of work you can do remotely with little or no knowledge of the clients business, IT setup, processes or culture.

But anyway, after you identify the sources you move on to the next step.

Check data availability

Here you discuss aspects of the data you require with the database / application platform owners to ensure that:

  1. they have the data you are looking for
  2. that quality of the data is known and data quality can be addressed
  3. that the data is relevant for what is needed
  4. that the cost of providing this data is not prohibitive
  5. that this data can be made available to you
  6. that service levels could be put in place, if and when required

So far so good. Once passed these hurdles (and don’t forget this is a super-simplification) we move in to the next.

Make proof of concepts

So, now we know:

  1. What data we need
  2. Where we can get it from
  3. How we get it
  4. What we need to do to make it usable
  5. How we need to analyse it

Therefore, we go ahead and create a proof of concept or three. Simples!

However, make sure that all prototypes are governed by these simple timeless guidelines:

  1. The proof of concept should be small enough to be doable in a reasonable time-frame. I would be rather generous for the very first pilot of its type in a company, but would set that limit at 90 days, tops.
  2. Make sure that the proof of concept is big enough to be significant. Again, ‘simple enough to be realisable’ and ‘large enough to be significant’, should go hand in hand.
  3. Arrange your proof of concept execution into sprints. So your 90 days may be made up of nine 10 day sprints.
  4. Don’t try and shoe-horn infrastructure aspects of your initiative into sprints, it just doesn’t work, and simply pisses people off.
  5. If a proof of concept looks like it will fail, then make sure it fails early. There’s nothing worse than having people insist on pushing a dead project to live the full length of its planned term. Failing early means that business doesn’t take a dim view of the pilot, and will be more open to new proof of concept initiatives.

Analyse the outcomes

You run your proof of concept. You analyse, assess and represent your outcomes. You socialise, present and interpret.

Revise your strategic outlook accordingly

When you’ve done that you are in now in a good position to estimate the usefulness of the exercise, from both a qualitative and quantitative perspective.

Did I mention technology?

I did not want to touch in specific aspects of technology in this piece, in part, because I did not consider it a central issue in the theme of things. Of course, as part of creating proofs of concepts and pilot schemes you may want to experiment with the swatch (swaith? oh for auto-correction) of technologies out there. So go ahead and evaluate ‘Big Data’ technologies, and don’t forget, the answer to every Big Data technology question isn’t an automatic ‘Hadoop’. There are other valid Big Data technology options around, such as Lustre and GPFS, or even Oracle, Teradata or EXASol. Also, remember this, if all you are working on is a prototype, a proof of concept or a pilot then you can try and negotiate a free license with any of the major DBMS vendors for that initiative. So negotiate, bargain and get the most appropriate technologies with the best deals.

That’s all folks

Finally I will leave you with three guidelines to consider:

  1. Don’t ask ‘how can I do Big Data?’ but ‘what data do we need?’
  2. You don’t need to seek out Big Data. If you really need it, and it’s available, and it’s adequate and appropriate, then you’ll be getting it soon enough.
  3. Avoid searching for a Big Data problem you don’t have, which can only be solved by Big Data technology you don’t need.

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:

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.

Absolutely Fabulous Big Data Roles

03 Monday Aug 2015

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

≈ 1 Comment

Tags

Big Data, Consider this, goodstart, Martyn Jones, Strategy

Plus ça change, plus c’est la même chose.

Jean-Baptiste Alphonse Karr

Prologue

I wrote a piece called ‘7 New Big Data Roles for 2015′. I published it on LinkedIn. Many people read it. Some people made suggestions. Others politely ignored it.

I listened to the suggestions, comment and criticisms, and revised the piece as a result.

So here, it is… I hope you like it. And if not, I might try again in six months’ time. Continue reading →

Amazing Data Warehousing with Hadoop and Big Data

26 Sunday Jul 2015

Posted by Martyn Jones in Big Data, Consider this, Data Warehousing, good start, goodstart, hadoop

≈ Leave a comment

Tags

Big Data, cloudera, enterprise data warehousing, goodstart, hadoop

Many thanks for reading, and don’t forget, please join The Big Data Contrarians.

Some time back, Bill Inmon, the father of Data Warehousing, took the Hadoop vendor Cloudera to task for putting out some confusing advertising.

In recent times, Cloudera have linked up with Ralph Kimball, who, as some in the data world will know, has been an eternal ‘rival’ of Bill Inmon.

For some, the name of Ralph Kimball has become synonymous with dimensional modelling, and although the Kimball Group once stated that Ralph did not invent the original basic concepts of facts and dimensions, Ralph has contributed much to the development of dimensional modelling and the innovative use of SQL. Subsequently, the Kimball Group reassessed, and are now labelling Ralph as the “Dimensional modelling inventor”.

Kimball and Cloudera have collaborated on a number of initiatives, such as a webinar and slide set, with particular emphasis on the theme of Hadoop and Data Warehousing.

Now, I do not know whether this is intentional or accidental, but this collaboration has produced a lot of disingenuous claims and dubious comparisons, so much so, that I get the impression that building the DW Disinformation Factory is becoming a cottage industry in its own right.

Personally, I can see scenarios in which Big Data complements Enterprise Data warehousing, and I have explained my vision and possible architectures for these scenarios. However, what some Hadoop vendors are alluding to in the Data Warehousing space, is actually quite mischievous and misleading and is not constructive in the least, in fact, the biggest side-effect is to muddy the Big Data and Data Warehousing waters even further. That is not good, either for the industry or for the customers, or indeed, for the professionals.

In one piece of content from Cloudera, we can read that…

“Dr. Kimball explains how Hadoop can be both:

A destination data warehouse, and also

An efficient staging and ETL source for an existing data warehouse”

On the first point? No, Hadoop will not be replacing Teradata, Oracle, EXASol or any other high-performance relational database management system.

On the second point. Hadoop could support a data source for Data Warehousing, as can many other technologies. However, there is no such animal as an ETL source. There are data sources and data targets, extractions, transformations and loads, and all that cool data management, but ETL is a technology, not a source.

I think Big Data may have a big future; it depends on how deeply the internet development culture pervades enterprise application development. A lot of what Big Data addresses is about is making up for shortfalls created by badly architected web applications and shoddy application development, in which data use and data persistence were at best workaround bodges, rather than being well designed and coherent approaches to data management.

Maybe this is some why people have a hard time explaining why they are considering using Hadoop technologies for Big Data. What would a CEO say if it was brought to their attention that Hadoop was being used in their business simply to make up for the fact that their internet applications are really shoddy examples of analysis, design, architecture and management? More to the point, what would the shareholders say if they understood the full ramifications behind the need to use Hadoop?

In many cases, I think that Hadoop can be an indication that your IT organisation did something very wrong in the past, and that in these cases Hadoop is the price one pays when you one does not want to bite the bullet and admit that to screwing up, big time.

In my opinion, it would make more sense to replace applications built on faulty architectures with robust and well-architected applications, rather than fix a problem by overmedicating the patient. This would mean that data generated and used by these applications could simply dovetail into standard decision-support data platforms, such as the Enterprise Data Warehouse.

As for Cloudera and their bizarre and babbling baloney about Hadoop replacing the Data Warehouse? I suggest they read a book in the subject of Building the Data Warehouse, and maybe buck up their ideas a bit. As Bill Inmon stated “You would think that the executives of Cloudera would have familiarized themselves with what a data warehouse is.”

As for recognised data professionals and influencers who support such Hadoop tripe? The less said the better. Eh, Ralphie?

That stated, maybe Cloudera, Kimball and the Big Data flim-flam merchants simply don’t care.

So go ahead, “turbocharge your Porsche – buy an elephant.”

Many thanks for reading. Don’t forget, please join The Big Data Contrarians. The best Big Data community on the planet.

You can’t hide your lyin’ Big Data

22 Wednesday Jul 2015

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

≈ Leave a comment

Tags

Big Data, good start, Good Strat, goodstart, goodstrat

As a child, I adored the USA rock band the Eagles, especially the musical talents of Joe Walsh. This explains the inspiration behind the title of this piece.

So, what’s going down at Ashley Madison?

Never heard of them? Off your radar? Surely not?

That stretches the bounds of incredulity. As even the people in Singapore’s Media Development Authority have heard of them. They even described their business site this way “it promotes adultery and disregards family values”, and subsequently will not allow them to operate in Singapore. Well, what a turn-up for the books.

On a more serious note, and as you might know, (from Wikipedia or some other ‘sites’,) Ashley Madison is a Canadian-based online dating service and social networking service marketed to people who are married or in a committed relationship. Its slogan is “Life is short. Have an affair.” It seems, if we are to believe various reports doing the rounds, that their Big Data has been compromised, big time.

Yes, I know, how could that possibly have happened, right?

According to some reports, Adison Mashley have around 37 million clients in the Big Data pool, and large caches of it have allegedly been stolen after an apparently successful hacking attempt was carried out. According to Krebs On Security, data stolen from the web site in question “have been posted online by an individual or group that claims to have completely compromised the company’s user databases, financial records and other proprietary information.”

But, again I ask, how can this happen?

I am not an avid fan of Big Data technology for core business use, and given the level of Big Data technology maturity, it sounds like a dopey idea. But each to their own.

What I will state is that my database management experience has tended to be associated with database technologies that can only be hacked as part of an inside job i.e. where people either know user IDs, passwords, IP addresses and layers of protection etc. or know of someone who does. Either someone who is a friend, part of the family (no, not that type of ‘family’) or someone who can be blackmailed into divulging the required access paths and security check workarounds.

However, taking a broader and more permissive view of this alleged hackerisation of Big Data, do we write it up as a Big Data success, i.e. The Amazing Big Data Affair? Put it down to a technical glitch and community faux pas? Or do we take a jaundiced view of the whole thing and keep it real? I await with baited breath for the enlightened opinions of the Big Data gurus.

Mitch ‘n’ Andy are not unfamiliar with ‘issues’ related to the use of people’s data. The Daily Dot carried a piece from contributing writer S. E. Smith with the headline ‘Why Ashley Madison is cheating on its users with Big Data’ in that piece, Smith states that “Like pretty much every other website on Earth, Ashley Madison spies on its users and crunches the data in a variety of ways to increase the bottom line.”

Belinda Luscombe writing in Time confirmed these suspicions with a piece titled ‘Cheaters’ Dating Site Ashley Madison Spied on Its Users’. She wrote:

In a study to be presented at the 109th Annual Meeting of the American Sociological Association in San Francisco on Saturday Aug. 16, Eric Anderson, a professor at the University of Winchester in England claims that women who seek extra-marital affairs usually still love their husbands and are cheating instead of divorcing, because they need more passion. “It is very clear that our model of having sex and love with just one other person for life has failed— and it has failed massively,” says Anderson.

“How does he know this? Because he spied on the conversations women were having on Ashley Madison, a website created for the purpose of having an affair. Professor Anderson, who as it turns out is a the “chief science officer” at Ashley Madison, looked at more than 4,000 conversations that 100 women were having with potential paramours. “I monitored their conversation with men on the website, without their knowing that I was monitoring and analyzing their conversations,” he says. “The men did not know either.”

Elsewhere, and as reported on Wikipedia, “Trish McDermott, a consultant who helped found Match.com, accused Ashley Madison of being a “business built on the back of broken hearts, ruined marriages, and damaged families.”

Wow, wow, and triple wow! What a way to run a dance hall!

Maybe they should reconsider their slogan, making it more snappy and apposite. How about “Life is short, we pimp your Big Data” as a starter? So go ahead, make your own and post it below. Have fun.

Many thanks for reading.

Oh, and one last thing before I go… GOOD-AD: Join The Big Data Contrarianshttps://www.linkedin.com/grp/home?gid=8338976

← Older posts
Follow GOOD STRATEGY on WordPress.com

Top posts

  • Myth-busting: Data Mesh and Data Warehousing - Revisited
  • Why I called bullshit on the data lakehouse nonsense
  • The World's Best Data Quotes... Including Big Data quotes
  • Data warehousing explained to big-data, data-lake & data-lakehouse folk
  • USA: What Trumped Hillary?
  • Extracts: And, what would the Ladies and Gentlemen like?
  • Reality Check: Data Mesh and Data Warehousing  
  • 7 New Big Data Roles for 2015
  • The Big Data Contrarians: The Agora for Big Data dialogue
  • Top 10 Amazing Big Data Gurus That All Amazing Big Data Gurus Should Know

Enter your email address to follow this blog and receive notifications of new posts by email.

Join 2,336 other subscribers

Names in the cloud

4th generation Data Warehousing All Data Ask Martyn Big Data Big Data 7s Big Data Analytics Business Intelligence business strategy Consider this dark data data architecture Data governance Data Lake data management data science Data Supply Framework Data Warehouse Data Warehousing Good Strat goodstrat Good Strategy IT strategy Martyn does Martyn Jones Martyn Richard Jones pig data Politics Strategy The Amazing Big Data Challenge The Big Data Contrarians

The Good Strat Archives

  • January 2022
  • December 2021
  • November 2021
  • June 2020
  • May 2020
  • April 2020
  • March 2020
  • July 2019
  • June 2019
  • May 2019
  • December 2018
  • January 2018
  • December 2017
  • October 2017
  • August 2017
  • July 2017
  • June 2017
  • May 2017
  • April 2017
  • March 2017
  • February 2017
  • January 2017
  • December 2016
  • September 2016
  • August 2016
  • May 2016
  • March 2016
  • February 2016
  • January 2016
  • December 2015
  • November 2015
  • August 2015
  • July 2015
  • June 2015
  • May 2015
  • April 2015
  • March 2015
  • February 2015
  • January 2015
  • December 2014
  • November 2014
  • October 2014
  • September 2014

The Stats

  • 98,867 hits

Recent posts

  • Data Trailblazers: 2022 Vision January 2, 2022
  • Tea with The Data Contrarian: Afilonius Rex December 10, 2021
  • Reality Check: Data Mesh and Data Warehousing   December 5, 2021
  • Myth-busting: Data Mesh and Data Warehousing – Revisited November 25, 2021
  • Heaven help us! Have you seen the latest Virtual Data Warehouse bullshit? June 26, 2020
  • DATA! STRATEGY, INNOVATION AND VALUE BULLSHIT June 9, 2020
  • Big data’s unvirtuous circus and twelve v-words May 17, 2020
  • Laughing at Big Data – What’s on the inside May 16, 2020
  • Why I called bullshit on the data lakehouse nonsense May 16, 2020
  • Laugh at Big Data – download my ebook for free on 17th May. May 16, 2020

Hours & Info

Martyn Richard Jones
Madrid, Spain
+33 767 120 160
10:00 - 17:00
Follow GOOD STRATEGY on WordPress.com

Follow me on Twitter

My Tweets

Top Good Strat Posts & Pages

  • The Good Strategy Company
  • Myth-busting: Data Mesh and Data Warehousing - Revisited
  • Why I called bullshit on the data lakehouse nonsense
  • The World's Best Data Quotes... Including Big Data quotes
  • Data warehousing explained to big-data, data-lake & data-lakehouse folk
  • USA: What Trumped Hillary?
  • About
  • Extracts: And, what would the Ladies and Gentlemen like?
  • Reality Check: Data Mesh and Data Warehousing  
  • 7 New Big Data Roles for 2015

Good strat tag cloud

accountability advertising All Data Analytics aspiring tendencies in IM awareness Banking Behavioural Economics BI Big Data Bill Inmon Brexit BS Business business analysis Business Enablement business intelligence Business Management business strategy Challenges Commercial IT Consider this corporate assets Corporate IT Creativity data data analytics data architecture data integration data management Data Marts data science Data Warehouse Demagogism Dogma DW 3.0 Economics enterprise data warehousing EU Financial Goal Setting goodstart good start Good Strat goodstrat Good Strategy hadoop Information and Technology information management Information Technology IT business IT Strategy knowledge management leadership marketforces Marketing Martyn Jones Martyn Richard Jones MDM Offshoring operationalwareness Organisational Autism organisational awareness Outsourcing Pimps Politics project management Requirements management Risk Risk Management statistics Strategy trading traditional assets UK

Categories

  • 4th generation Data Warehousing
  • accountability
  • advertising
  • agile
  • agile way of working
  • agile@scale
  • AI
  • All Data
  • Analytics
  • anthropology
  • Architecture
  • Artificial Intelligence
  • Ask Martyn
  • Assets
  • awareness
  • bad strategy
  • Banking
  • behaviour
  • Best principles
  • Big Data
  • Big Data 7s
  • Big Data Analytics
  • blockchain
  • Books with influence
  • Brexit
  • BS
  • business
  • Business Intelligence
  • business strategy
  • Cambriano
  • Cambridge Analytica
  • China
  • Climate Change
  • Cloud
  • code of conduct
  • Commercial Analytics
  • community
  • Condiser this
  • Conservative Party
  • consider
  • Consider this
  • Consultation
  • Creativity
  • dark data
  • data architecture
  • Data governance
  • data hub
  • Data Lake
  • data management
  • Data Mart
  • data mesh
  • data science
  • Data Supply Framework
  • Data Warehouse
  • Data Warehousing
  • deceit
  • deep learning
  • Democracy
  • digital transformation
  • Diplomacy
  • disinformation
  • Dogma
  • Duties
  • DW 3.0
  • ECM
  • Economics
  • EDW
  • England
  • enterprise content management
  • ethics
  • EU
  • Europe
  • European Union
  • Excellence
  • Excerpt
  • Executive
  • Extract
  • Federalism
  • Financial Industry
  • fraud
  • Freedoms
  • Globalisation
  • good start
  • Good Strat
  • Good Strategy
  • Good Strategy Radio
  • goodstart
  • goodstartegy
  • goodstrat
  • goostart
  • governance
  • hadoop
  • hdfs
  • HR
  • humour
  • India
  • influencers
  • informatio Supply Framework
  • information
  • Information Management
  • Information Supply Frameowrk
  • Information Supply Framework
  • Infotrends
  • Inmon
  • instruments
  • IoT
  • IT Circus
  • IT fraud
  • IT strategy
  • IT World
  • iterations
  • java
  • Knowledge
  • knowledge management
  • Labour Party
  • leadership
  • Leadership 7s
  • life
  • listening
  • literature
  • LSE
  • machine learning
  • Management
  • market forces
  • Marketing
  • Marty does
  • Martyn does
  • Martyn Jones
  • Martyn Richard Jones
  • media
  • Memory lane
  • Methodology
  • nationalism
  • nine competitive forces
  • no limits
  • Northern Ireland
  • obituary
  • Obligations
  • offshore
  • Offshoring
  • operational
  • Outsourcing
  • Oxford
  • pain
  • Parliament
  • Peeves
  • Personal Integrity Key
  • Philosophy
  • pig data
  • PIK
  • PIR
  • Plaid Cymru
  • Planning
  • poem
  • poems
  • Poetry
  • Polemic
  • political science
  • Politics
  • pomo
  • postmodern
  • POTUS
  • Process
  • Professional Networking
  • professionalism
  • project management
  • Project to Excel
  • prose
  • public
  • Public Integrity Record
  • Quiz
  • Rant
  • Referendum
  • Remain
  • RIghts
  • Risk
  • Rivalry
  • Russia
  • Ruth Davidson
  • Sales
  • satire
  • Scotland
  • Scottish National Party
  • scrum
  • sentiment analysis
  • SMILES
  • Snippet
  • SNP
  • Social
  • Social Media
  • Sociology
  • spoof
  • statistics
  • Stories
  • Strategy
  • structured intellectual capital
  • supply chain management
  • tactics
  • Tax avoidance
  • Tax evasion
  • TEAM
  • technology
  • The Amazing Big Data Challenge
  • The Big Data Contrarians
  • The Greens
  • The Guardian
  • The hidden wealth of nations
  • Trade
  • UK
  • Uncategorized
  • United Kingdom
  • USA
  • Value
  • Wales
  • wisdom

Blog at WordPress.com.

  • Follow Following
    • GOOD STRATEGY
    • Join 131 other followers
    • Already have a WordPress.com account? Log in now.
    • GOOD STRATEGY
    • Customize
    • Follow Following
    • Sign up
    • Log in
    • Report this content
    • View site in Reader
    • Manage subscriptions
    • Collapse this bar
 

Loading Comments...
 

    Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
    To find out more, including how to control cookies, see here: Cookie Policy