Tag Archives: Dimensional Modeling

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

04 Wednesday Feb 2026

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

30 Friday Jan 2026

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

10 Saturday Jan 2026

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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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