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Tag Archives: Enterprise Data Warehouse

Podcast Episode: Building A Data Logistics Hub

25 Tuesday Aug 2026

Posted by Martyn Rhisiart Jones in Architecture, data architecture, Data governance, data hub, data management, data mesh, data science, Data Supply Framework, Data Warehouse, Data Warehousing

≈ 2 Comments

Tags

data architecture, data governance, data integration, data-logistics-hub, Enterprise Data Warehouse, Podcast

Futuristic data center labeled Central Logistics Hub, with glowing data routes, servers, and operators
Glowing data pathways weave through a multi-level logistics hub filled with servers and operators.

Pip: If you have ever looked at your organisation’s data landscape and thought “this resembles a motorway junction designed by someone who hates drivers,” then Martyn Jones has a blueprint with your name on it.

Mara: This episode follows a series of posts introducing the Data Logistics Hub — covering what the concept is, why the pain points are real, how strategy and architecture hold it together, and what the actual components look like in practice.

Pip: Let’s start with the foundations — what the hub is and why it exists.

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DATA WORLD: Data Warehouse Action: Big Business Drivers

11 Wednesday Feb 2026

Posted by Martyn Rhisiart Jones in Inform, educate and entertain.

≈ 2 Comments

Tags

business intelligence, business strategy, data architecture, data governance, data management, Data Warehouse, data-strategy, Enterprise Data Warehouse

Masterclass on the side!

Martyn Rhisiart Jones

Madrid, Saturday 31st January 2026

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

11 Wednesday Feb 2026

Posted by Martyn Rhisiart Jones in Big Data, Consider this, Data Warehousing, Good Strat, hadoop, hdfs, Martyn Jones

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Tags

Big Data, business intelligence, data architecture, data integration, Data Warehouse, data-strategy, Enterprise Data Warehouse, ETL

Martyn Rhisiart Jones

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

10 Tuesday Feb 2026

Posted by Martyn Rhisiart Jones in Inform, educate and entertain.

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Tags

business intelligence, Data Catalog, data governance, data management, Data Modeling, Data Quality, Data Warehouse, data-strategy, Enterprise Data Warehouse

Martyn Rhisiart Jones

Zamora, Tuesday 10th February 2026

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.

Continue reading →

DATA WORLD: Understanding the Data Warehouse Dilemma – 2026/02/07

06 Friday Feb 2026

Posted by Martyn Rhisiart Jones in Inform, educate and entertain.

≈ 1 Comment

Tags

business intelligence, data architecture, data governance, Data Modeling, Data Quality, Data Warehouse, data-strategy, Enterprise Data Warehouse

Martyn Rhisiart Jones

Madrid, Saturday 7th February 2026

Books from Martyn Rhisiart Jones https://www.amazon.es/stores/author/B086K5B97Y

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.

But this was the coup de grace: “Databricks is a unified data platform that can behave like a data warehouse.” 

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Requirements – Building the Data Warehouse – Part II

01 Sunday Feb 2026

Posted by Martyn Rhisiart Jones in Data Mart, Data Supply Framework, Data Warehouse, Data Warehousing, DW 3.0, EDW, Inform, educate and entertain., Masterclass

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Tags

business intelligence, data architecture, data governance, Data Mart, Data Modeling, Data Warehouse, Enterprise Data Warehouse, ETL, Requirements Engineering

The Good Strat Masterclasses

Masterclass Mode Engaged

Martyn Rhisiart Jones

Madrid, Sunday 1st February 2026

PART I

PART II

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DATA WORLD: Requirements – Building the Data Warehouse – Part I

30 Friday Jan 2026

Posted by Martyn Rhisiart Jones in Inform, educate and entertain.

≈ 1 Comment

Tags

business intelligence, data governance, data management, Data Mart, Data Warehouse, data-strategy, Dimensional Modeling, Enterprise Data Warehouse, Requirements Engineering

The Good Strat Masterclasses

Masterclass Mode Engaged

Martyn Rhisiart Jones

Madrid, Sunday 1st February 2026

PART I

PART II

Happy Sunday to one and all. As many of you will know, I have been intimately involved in designing, building, and delivering data warehousing and advanced analytics initiatives for more than 35 years.

Today, I will take a deep dive into requirements gathering for a new iteration of an enterprise data warehouse and a new data mart.

Establishing a case for a new data warehouse iteration is part of the requirements-gathering phase of a project. This must always be at the forefront of the exercise and a continuous question we must ask ourselves. We must always consider the answer to the question “To what ends?”

First, before diving into the core aspects of the iteration, we will examine the legitimate drivers and objectives for data warehouse initiatives. The prerequisite skills, knowledge, and experience needed to carry out this activity successfully, and, after that, we will look at the preparation required to align the personal, business, and technological effectiveness and success of the initiative.

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Top Influencer Mode – Masterclass Content

30 Friday Jan 2026

Posted by Martyn Rhisiart Jones in Inform, educate and entertain.

≈ Leave a comment

Tags

data architecture, data governance, data management, data mesh, Data Modeling, data-strategy, Enterprise Data Warehouse, Master Data Management

Subject Areas

Masterclass Mode – Requirements Gathering

Subject areas serve as the foundational blueprints of modern data management, organizing an enterprise’s vast ocean of information into logically related, manageable domains (such as Customer, Product, Order, or Employee). By grouping data around core business entities rather than isolated applications or departmental silos, subject areas create a shared language and structure across the organization.

Here is how subject areas function across the core pillars of data strategy:

  • Data Architecture: Establishes high-level conceptual data models (Enterprise Data Models) that define key entities, their attributes, and their relationships to ensure systems are built with structural integrity and scalability.
  • Data Management: Directs operational workflows. such as data integration, master data management (MDM), and data quality monitoring, by grouping technical assets around business-aligned domains.
  • Data Governance: Assigns ownership, data stewardship, access controls, and compliance policies to specific domains, ensuring clear accountability for data quality, privacy, and security.
  • Technology & Platform Engineering: Guides system design choices, domain-driven architectures (such as Data Mesh), storage partitioning, and API boundaries to align IT infrastructure directly with business operations.

By bridging business concepts with technical execution, subject areas ensure that data assets are consistently defined, securely managed, and easily leveraged to drive decision-making.

Navigating Data Warehousing’s Professional Crisis – 2026

13 Tuesday Jan 2026

Posted by Martyn Rhisiart Jones in Snippet

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Tags

business intelligence, data architecture, data governance, Data Warehouse, data-engineering, data-strategy, Enterprise Data Warehouse, IT Consulting, Professional Ethics

Martyn Rhisiart Jones

Read my absolutely fabulous books: http://www.goodstrat.com/books
 
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.
 

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A Brief History of Data Warehousing – 2026/01/07 – Includes Podcast

10 Saturday Jan 2026

Posted by Martyn Rhisiart Jones in Masterclass, Snippet

≈ 2 Comments

Tags

Bill Inmon, business intelligence, data architecture, Data Modeling, Data Vault, Data Warehouse, Dimensional Modeling, Enterprise Data Warehouse, Ralph Kimball

Martyn Rhisiart Jones

Madrid, 7th January 2026

The origins of data warehousing are often pinned to the late 1980s, when the term “business data warehouse” first appeared in an influential IBM Systems Journal article by researchers Barry Devlin and Paul Murphy. I was based in Birmingham at that time, and I also wrote a similar foundational document on Information Centres for Sperry Univac.

Yet, as with many technological breakthroughs, the story is far richer and older than the conventional narrative suggests. The foundational components of what we now recognise as a data warehouse were quietly taking shape as early as the 1960s, driven by the need to organise, integrate, and analyse growing volumes of business information in an era of punch cards, magnetic tape, and the first mainframes.

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Why IT Must Speak the Language of Business – Remaster 2026

21 Sunday Sep 2014

Posted by Martyn Rhisiart Jones in Business Intelligence, Data Warehouse, Extract

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Tags

business intelligence, Business-IT Alignment, data architecture, data governance, Data Warehouse, Enterprise Data Warehouse, IT Strategy, requirements-gathering, Tech Satire

Extract taken from the draft work-in-progress provisionally titled Assess! Choose! Act! Data Warehousing and Strategy by Martyn Jones, Chief Strategist at Cambriano Energy.

For more than 34 years I have been trying to convince IT organisations that it is not in their best interests to play Santa Claus, especially when it comes to strategy and data management.

Peace. Tranquility. Mastery.
Peace. Tranquility. Mastery.

I have tried – again and again, to make people pay attention to this advice, because I think that acting upon this take-away in an intelligent manner is absolutely central for the success of IT, for the benefit of business, and ultimately for the effective realization of Information Management; whether that is Data Warehousing, Business Intelligence, Data Integration, Decision Support, Data Analytics, Big Data or MDM.

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A Brief History of Data Warehousing

14 Sunday Sep 2014

Posted by Martyn Rhisiart Jones in Snippet

≈ Leave a comment

Tags

Bill Inmon, business intelligence, data architecture, Data Modeling, Data Warehouse, data-engineering, Enterprise Data Warehouse, information management, Ralph Kimball

There is a general consensus that Data Warehousing first appeared in the 1980s. However, the components of Data Warehousing were being developed and implemented as early as the 1960s. Many individuals are credited with discovering Data Warehousing. Wikipedia has a great chronological timeline that provides a lot of context for the evolution of data warehousing methodologies.

Continue reading →

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