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Tag Archives: Data Modeling

MASTER CLASS: Mastering Data Warehousing: Balancing Pre-Emption and Back-Filling

24 Tuesday Mar 2026

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

≈ 1 Comment

Tags

data architecture, data governance, data management, Data Modeling, Data Warehouse, data-engineering, data-strategy, ETL

Martyn Rhisiart Jones, Madrid Tuesday 24th March 2026

In the ever-evolving world of enterprise data warehousing, one of the most persistent and critical challenges is how to intelligently expand subject areas and the associated data within the core data warehouse database, while maintaining architectural integrity, data quality, and governance, without venturing into data mart considerations.

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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.

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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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MASTERCLASS: What Are Surrogate Keys? – 2026/02/04

04 Wednesday Feb 2026

Posted by Martyn Rhisiart Jones in data mesh, data science, Data Supply Framework, Data Warehouse, Data Warehousing, Inform, educate and entertain., information, Information Supply Framework, Knowledge, knowledge management, Martyn Jones, Masterclass

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Tags

data architecture, Data Modeling, Data Warehouse, data-engineering, Database Design, Dimensional Modeling, Primary Keys, surrogate-keys

Martyn Rhisiart Jones, Madrid, 4th February 2026.

Introduction

In data modelling and database design, keys play a fundamental role in uniquely identifying records and defining relationships between tables. One of the most widely used types of keys, especially in analytical systems and data warehouses, is the surrogate key.

A surrogate key is an artificial, system-generated identifier assigned to a record in a table. It is typically used as the primary key. It has no business meaning or semantic relationship to the real-world entity it represents. Common implementations include auto-incrementing integers or globally unique identifiers (GUIDs).

Surrogate keys exist purely to serve the needs of the database system: performance, stability, and simplicity.

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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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Top Influencer Mode – Masterclass Content

30 Friday Jan 2026

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

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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.

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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Mastering Data Language for Better Architecture

15 Tuesday Oct 2024

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

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Tags

Communication, data architecture, data management, Data Modeling, data-design, data-strategy, Enterprise Architecture, Information Architecture

To know data, you must know the lingo

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.

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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.

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