The relations between Wales, Judaism, and Zionism weave a tale as old as the hills. It is as tangled as the roots beneath them. These are threads of scripture, sympathy, small nations’ stubborn fire, and biblical thunder from the valleys. This comes to us in the voices of the past; lyrical, rhythmic, overflowing with vivid, swirling imagery. Alliteration and a bardic, almost incantatory prose describe the green and golden hills of Wales. The chapels rang with the thunder of prophets. The psalms rolled like the sea in the lungs of the miners. There, the Old Testament burned brighter than the coal seams! On those Nonconformist mornings, the children learned about Jerusalem. They learned their names even before their own rivers. Jordan flowed through the hymns. Zion was no distant dream but a living pulse in the blood.
Me: What do you make of Martyn Jones of goodstrat.com’s views on big data, are they correct, close or not true?
[Grok thought for a while]
Grok: Martyn Jones (of goodstrat.com) is one of the sharpest, most entertaining data contrarians out there. He’s been calling “Big Data” mostly bullshit since around 2014–2015, long before it became fashionable to say so. His Core Views (in his own blunt style): The whole 2010s Big Data circus (Hadoop, the 3Vs turned into 12 Vs including Vagueness, Vendibility, Vulgarity, etc.) was 80–90% vendor hype, consultant grift, and marketing snake oil. Most companies didn’t (and still don’t) have Google/Facebook-scale problems. Chasing petabytes of unstructured social media noise often distracted companies. They were diverted from cleaning and using the high-value operational data they already had.
In the quiet underbelly of corporate life, sanctioned software often lags behind real needs. Shadow apps, which are unsanctioned tools employees adopt on their own, continue to flourish. Nowhere is their value more pronounced than in data analytics. Teams quietly sidestep lengthy procurement and rigid platforms. They harness spreadsheets, personal BI instances, open-source scripts, and cloud sandboxes. Far from mere rebellion, these shadow practices reveal institutional shortcomings while delivering tangible gains. Here are seven compelling advantages, viewed through a lens that values both ingenuity and measured reflection.
We asked seven highly engaged professionals for their top advantages of allowing Shadow Apps to thrive. We then requested comments from industry leaders. And here is what they told us.
Building the Data Logistics Hub: Pieces and Parts – 2026/02/15 – Part 3
Guide
This episode provides a comprehensive framework for the third installment in the series on the Data Logistics Hub (DLH). Martyn Jones conceptualised it as a technology-agnostic, centralised platform. Its purpose is efficiently moving, governing, and distributing data across organisations. This part expands on Part 1 (Challenges and Opportunities) and Part 2 (The Strategy). It focuses on the tangible “pieces and parts” of the DLH architecture. It outlines mandatory and optional elements. The episode also explores potential technologies. It examines key processes such as data pulling or pushing, translation from source to target, mapping, and data catalogues.
Building the Data Logistics Hub: The Strategy – 2026/02/14 – Part 2Before I begin, remember this: “All data roads lead to the Data Logistics Hub.” They also lead from it. It is the Rome of the age of data, information, knowledge, and wisdom. Be prepared!
Okay, we will now examine the Data Logistics Hub in terms of strategy, execution plans, and roadmaps.
A high-level blueprint for a successful Data Logistics Hub outlines several requirements. These include principles, guiding objectives, an imagined “better world” and organisational alignment. Key trade-offs must also be considered, such as centralised versus federated and batch versus streaming, among others.
Oh, marvellous. Valentine’s Day is tomorrow, the fourteenth of February, twenty twenty-six. The nation is already knee-deep in the annual ritual of manufactured affection. There’s pink packaging everywhere and the faint whiff of desperation lingers. And now, because apparently one layer of cynicism isn’t enough, we’re adding this so-called Celtic mysticism. It’s as if it’s the missing ingredient that turns a cynical cash-grab into something profound and ancient. How delightfully Welsh of us. We can’t resist a bit of mythic bollocks to make the whole thing feel less embarrassing.
Ah, cariad, let us speak now in the shadowed cadence of the valleys. The voice rolls like the Tawe after rain. It is rich and resonant, a little rough at the edges yet velvet beneath. Burton might have murmured it after one too many whiskies. Or Hopkins in that quiet, measured thunder waits. Patient as stone, it strikes. And through it all, the ghost of Dylan himself weaves words like nets of starlight over Talacharn’s black waters. Gwynfor’s steady, unyielding fire burns low and true for the land. It is more than soil and more than song. It is memory made flesh.
If Data and Information were our Valentine’s sweetheart, she would be fierce and elusive. She would not be some simpering rose but a wild thing of the Welsh hills. She would be ancient and newborn, speaking in cynghanedd of numbers and patterns. Her breath would be the soft hiss of wind through bracken.
We would woo her thus, yn Gymraeg ac yn Saesneg entwined, with the lilt that carries the green pulse of Cymru beneath every syllable:
Estaba leyendo un artículo escrito por Jeff Wilts y recomendado por Bill Inmon. Llegué a esta afirmación: «Teradata es un almacén de datos empresarial con todas las funciones». Para mí, la cosa fue aún más cuesta abajo a partir de ahí.
Pero esto fue el golpe de gracia: «Databricks es una plataforma de datos unificada que puede comportarse como un almacén de datos».
In this episode, we begin by honestly examining the pain points that make data logistics so difficult today. The challenges are siloed data and systems. There are also many data interchange point solutions. Quality is inconsistent, and there are security and compliance barriers. Additionally, data volumes are exploding. We then explore the transformative opportunities. These include faster time-to-insight and seamless collaboration across teams and organisations. The opportunities also feature monetisable data products and AI-ready flows.