Building the Data Logistics Hub: Pieces and Parts – 2026/02/15 – Part 3

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This is the brave new world of data!

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.

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Building the Data Logistics Hub: The Strategy – 2026/02/14 – Part 2

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This is the brave new world of data!


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.

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CONSIDER THIS: Celtic Mysticism Meets Valentine’s Day

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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.

Celtic mysticism on Valentine’s Day.

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Saint Valentine’s Day – Romancing the Data – 2026/02/14

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To Begin at the Beginning

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:

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Solucionando el Dilema del Almacén de Datos

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Martyn Rhisiart Jones

Libros de Martyn Rhisiart Jones: https://www.amazon.es/stores/author/B086K5B97Y

¿Qué decir?

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».

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Building the Data Logistics Hub: The Challenges and Opportunities – 2026/02/13 – Part 1

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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.

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Building the Data Logistics Hub: Easy Introduction – 2026/02/12 – Part 0

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This Is Going To Be Absolutely Fabulous!

Hold up there for a moment. Have I got something for you!

I may not be the father of Information Centres. I’m certainly not going to claim any of Bill Inmon’s achievements as my own. However, I have spent a professional lifetime wading in the data and information garlic. So, I do claim a rightful share of the credit.

And I am rightfully credited with founding the Data Logistics Hub design movement.

In an era where data is the lifeblood of organisations, it fuels decisions and powers AI. It enables innovation. It drives competitive advantage. The ability to move, integrate, share, and utilise that data efficiently has become a strategic imperative. Yet many enterprises still struggle with fragmented pipelines and siloed sources. They face compliance headaches and latency issues. There is also the sheer complexity of connecting data across clouds, on-premises systems, partners, and ecosystems.

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DATA WORLD: Data Warehouse Action: Big Business Drivers

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Masterclass on the side!

Martyn: The Enterprise Data Warehouse should be driven by business demand and nothing else.

Ed: What does that mean in practice?

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DATA WORLD: Friends! Romans! Countrymen! Big Data is not Data Warehousing – 2026/01/29

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29th January 2026

Hold this thought: To paraphrase the great Bob Hoffman, just when you think that if the Big Data babblers were to generate one more ounce of bull**** the entire f****** solar system would explode, what do they do? Exceed expectations.

I am a mild mannered person. However, one thing that irks me is hearing variations on certain themes. These themes include phrases like “Data Warehousing is Big Data.” Another is “Big data is in many ways an evolution of data warehousing.” Lastly, some say “with Big Data you no longer need a Data Warehouse.”

Big Data is not Data Warehousing. It is not the evolution of Data Warehousing. It is also not a sensible and coherent alternative to Data Warehousing. No matter what certain vendors will put in their marketing brochures or stick up their noses.

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DATA WORLD: Fixing the Data Warehouse – 2026/02/10

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Martyn Rhisiart Jones

What to say?

I was reading an article. It was written by Jeff Wilts and recommended by Bill Inmon. I got to this statement: “Teradata is a full-featured enterprise data warehouse.”  For me, it went further downhill from there.

It was very disheartening and deceptive. I decided to write an article about my thoughts on it. (Understanding the Data Warehouse Dilemma – 2026/02/07, https://goodstrat.com/2026/02/06/understanding-the-data-warehouse-dilemma-2026-02-07/).

As a result, many people approached me. They asked directly and indirectly if I would suggest ways and means to overcome or avoid those dilemmas.

This is the result.

Enjoy! But even better, let me know what you think.

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