Laughing@Data.Com (often discussed alongside The 2030 Data Agenda essays and writings) is a satirical and polemical book by veteran data architect and consultant Martyn Rhisiart Jones.
Part memoir, part industry autopsy, and part manifesto, the book takes a witty and sharp look at the absurdity of the IT and enterprise data world. Rather than being another standard tech guide, it functions as a survival manual for anyone dealing with corporate tech hype cycles.
I would like to introduce you to a pragmatic approach to Big Data and Big Data Analytics. It is real-world focused and business-centric. This is the best approach to Big Data you are ever likely to find. Yet, I am still significantly understating the magnificent utility. It is also timely and has all the pertinent facets of the approach.
The End of the Fortress: Why the Future of Data is “Liquid”
By Martyn Rhisiart Jones | Madrid, 3rd February 2026
In a landmark session at the Welsh Academy, Sir Afilonius Rex sat down with Martyn Rhisiart Jones. They aimed to dismantle our outdated obsession with “data management.” The verdict? The era of the digital fortress is dead. In its place, a new paradigm of Cognitive Liquidity and Data Autonomy is emerging, redefining how we integrate global knowledge.
For most of its life in information technology, bolloxology has carried the faint smell of intellectual fart-like embarrassment. Too academic for product teams. Too rigid for startups. Too slow for an industry trained to ship first and rationalise later. Too smelly. It promised machines that could understand the world, and delivered, instead, a generation of beautiful bullshit diagrams and very little working software.
By 2026, that judgement looks increasingly wrong. Not because bolloxology suddenly got better, but because everything else did, and in doing so, exposed a missing layer in modern computing: meaning.
Ontology Didn’t Fail. The World Just Wasn’t Ready.
For most of its life in information technology, ontology has carried the faint smell of intellectual embarrassment. Too academic for product teams. Too rigid for startups. Too slow for an industry trained to ship first and rationalise later. It promised machines that could understand the world—and delivered, instead, a generation of beautiful diagrams and very little working software.
By 2026, that judgement looks increasingly wrong. Not because ontology suddenly got better, but because everything else did—and in doing so, exposed a missing layer in modern computing: meaning.
A quiet disquiet has settled over the once-confident corridors of enterprise data. What was, not so long ago, regarded as a rigorous and rather specialised craft, data warehousing and business intelligence, now frequently presents itself in a more casual, even improvisational guise. A growing number of senior executives, technology directors and indeed practitioners themselves confess to a mounting discomfort with the quality, and at times the sheer quantity, of self-proclaimed experts who populate the field.
Weaving the Dragon’s Data: A Welsh-Inspired Tale for Enterprise Architects in the New Year – 2026/01/01
The calendar turns to a fresh page in this crisp January of 2026. We, enterprise data and information architects, stand at a new threshold. Another year welcomes us, brimming with digital transformations. Data lakes swell like the River Taff after a storm. Information architectures evolve like the ancient mountain tops of Snowdonia. But amidst the algorithms and schemas, let’s pause for a moment of whimsy. What if we drew inspiration from the misty realms of Welsh myths and legends? Wales, that land of dragons and bards, offers a tapestry of stories. These stories mirror our quests: taming chaotic data into structured wisdom. They are about preserving cultural legacies in vast repositories. They ignite innovation from the sparks of history. In this Happy New Year ode, we’ll begin a narrative journey through Welsh lore. It is infused with the spirits of its iconic figures. Dylan Thomas, Dannie Abse, Richard Burton, Shirley Bassey, Paul Robeson, and Gwynfor Evans are part of this infusion. These spirits illuminate the art of data stewardship.
She sat where women had always sat. She was by the window and by the road. She was near the iron veins of the railway. Her hands were busy, her gaze soft. The love was in her eyes. The slow music of needles clicked and clacked like rain on Bethesda slate. In Wales, they would have called it cynefin, the comfort of the known. In Galicia, the way things have always been done. Magical, mysterious and mindful
A Dozen Data Wishes for Christmas 2025 — and a Sharper, Smarter New Year
As 2025 winds down, the tinsel comes out. It’s tempting to imagine a quieter, saner digital ecosystem on the horizon. Call it festive optimism or a data professional’s annual catharsis. Here are twelve wishes for 2026. They are equal parts hard-edged realism, FT Weekend reflection, and Wired-grade futurism.
Defining Goodstrat.com: A Strategist’s Digital War Room
In the sprawling digital bazaar of 2025 and the impending and interesting 2026, where every second-domain site peddles AI hype, data fakehouse, data mess or crypto snake oil, goodstrat.com stands out as a refreshingly unapologetic intellectual fortress.
It’s not a glossy corporate brochure. It is not a paywalled newsletter farm. It’s the online HQ of Martyn Richard Jones. He is a grizzled data, information and knowledge architect and self-styled “Data Shouterer-in-Chief.” He’s been dissecting the guts of information systems since the dial-up era.
Oh, brilliant. Gather round, comrades. It’s time for another installment of “Tech Executives Discover That Computers Need Electricity.” This time, they’ve dressed it up in a shiny frock and called it “2026 Data Trends.” Christ almighty, where do we even start?
Full-Private Number-One in the Awkward Squad of the rank and file of life was Sloppy, and yet had his glimmering notions of standing true to the Colours.
Charles Dickens, Our Mutual Friend
I am a sceptic, part of the awkward squad of troublemakers.
The awkward squad consists of people who ask questions and who won’t stop asking until they arrive at the crux of the matter.
The awkward squad won’t take bullshit for an answer.
The awkward squad are unquestioningly not pre-programmed to follow specific paths.
If anything, taxes for the lower and middle class and maybe even the upper-middle class should even probably be cut further. But I think that people at the high end – people like myself – should be paying a lot more in taxes. We have it better than we’ve ever had it.
Without a grounding in statistics, a Data Scientist is a Data Lab Assistant.
Martyn Jones
Hold this thought:There are big lies, damn big lies and data science with an AI chaser.
Statistics is a science, and some would argue that it is one of the oldest sciences.
Statistics can be traced back to the days of Augustus Caesar. He was a statesman, military leader, and the first emperor of the Roman Empire. Some set its provenance even earlier.
Indeed, suppose we accept that censuses are a part of statistics. In that case, we can trace history back to the Chinese Han Dynasty (2 AD). We can also consider the Egyptians (2,500 BC) and the Babylonians (4,000 BC).
Hold up, folks! You’re going to love these! They are amazing, beautiful, classy, dazzling and eminently readable. And that’s an absolute understatement of Mel Brook’s proportions.
As a writer, I have several works to my name. This post highlights some of these works. It also offers a quick link to the Amazon platform, where you can get your editions.
Data’s most significant challenges today are multifaceted and affect organizations across various industries. Here are some of the most important ones:
Narrator: To know data, you must know the grammar of data, information and knowledge. Depending on the language and its precision, accuracy, and richness, we will have a reasonable idea of approaching data and information modelling issues. To know data and information, you must understand the business well. People with a technical background and little or no business knowledge are often oblivious to their ignorance regarding business data and information. When you have a technician in the industry who doesn’t understand this, it’s a problem. If your technician is located thousands of kilometres from your company, it’s a disaster waiting to happen. Let’s listen to Pete and Dud wax lyrical about the importance of language and grammar.
The data warehouse is the place to copy exhaust data to
Martyn Jones, Bilbao, 2nd October 2024
Narrator: Not all data we have is related to strictly business domains such as products, organisation structure and corporate real estate. A lot of data we collect is simply about monitoring all aspects of IT, applications, networking, security and governance. To name just a few.
Dud: What’s all this data in my exhaust? Is my data back-end going well, or do I have a mechanical data governance issue? All this OLTP exhaust data is so tedious and tiring.
Narrator: According to some data-mesh folk, data warehousing is “a data management construct that dates back to the eighties,” I have a problem with that. It’s as if that was somehow a bad thing. Is it? For me, that’s quite a weak argument that, in a way, treats people as if they were idiots.
It is like someone asking Newton, “So, Sir Isaac, you don’t still believe in that old gravity nonsense, do you?”
Narrator: Another false meme doing the rounds is that Data Warehousing necessarily means monolithic databases. This is not what data warehouses have been for many businesses.
Why I called bullshit on the data lakehouse nonsense
I wrote an article that took to task purveyors of the data lakehouse nonsense. It got plenty of positive reactions and quite a few negative opinions. But what surprised me the most were the number of people who had already swallowed their pitch. Hook, line and sinker.
So why did I bother to express my opinions on the subject?
Martyn Richard Jones, Gif sur Yvette 23rd September 2017
Hi, Friends. As always, it’s great to be able to engage with you again. I am writing to you from the splendorous, wooded and verdant French town of Gif sur Yvette, and I wanted to take this opportunity to address aspects of data for an audience beyond the interests of data management and architecture people.
There is confusion about some of the fundamental aspects of business data, and there shouldn’t. If we strip away all of the boloney, it’s a subject that is quite approachable. In short, ‘it is not rocket surgery’. Continue reading →