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CONCEPTUAL DATA MODELLING

A Practitioner's Pocket Handbook

This book is 100% completeLast updated on 2026-05-07
Inderjit Singh Thind

Most data modelling books teach you the craft. This one teaches you the reality. Seven chapters of honest, practical guidance from real project experience — covering conceptual modelling, governance, enterprise challenges, and the human side of data work that nobody else writes about.

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About

About

About the Book

This is not a textbook. It is a practitioner's field guide written from real project experience, for anyone who works with data and wants to understand it properly before building anything.

Conceptual data modelling is where every successful data project begins. Before the schemas, before the databases, before the code, someone needs to sit down with the business and ask: what data do we actually have, what does it mean, and how does it all connect? This handbook shows you exactly how to do that.

Written in plain British English with real-world examples from the insurance domain, this pocket handbook covers the full conceptual modelling journey: from engaging stakeholders and extracting key concepts, through building your core artefacts, to navigating the governance, politics, and human challenges that no textbook prepares you for.

Seven focused chapters. No padding. Just honest, practical guidance you can apply from day one.

This is Volume 1 of an ongoing practitioner series. Volume 2 will go deeper into artefacts, templates, versioning, and a full worked case study including a real-world data migration scenario where conflicting definitions brought a project to its knees.

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Business AnalysisEnterprise ArchitectureSoftware ArchitectureData StructuresDatabasesData ScienceBusiness ArchitectureComputer Science

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About the Author

Inderjit Singh Thind

nderjit Thind has spent his career working at the intersection of business and data, helping organisations understand what their data actually means before they attempt to build anything with it. As an Enterprise Data Modeller and Data Architecture practitioner, he has worked across insurance, financial services, and the public sector, navigating the stakeholder relationships, governance challenges, and organisational complexities that technical training rarely prepares you for.

He holds a Master of Research (MRes) in Computer Science and is TOGAF Certified, bringing both academic rigour and hands-on architectural experience to his practice.

This handbook is the first in a series drawn from real project experience. It is written for data professionals who believe, as Inderjit does, that understanding the business always comes before designing the solution.

Contents

Table of Contents

TABLE OF CONTENTS

Conceptual Data Modelling: A Practitioner's Pocket Handbook  ·  Volume 1

Introduction Foreword
  • About this handbook and how to use it
  • The align, refine, and design framework
Chapter 1 What Is Conceptual Data Modelling?
  • 1.1   Definition and Purpose
  • 1.2   Where Conceptual Modelling Sits in the Lifecycle
  • 1.3   The Align Phase
  • 1.4   What Is and Is Not In Scope
Chapter 2 Building a Conceptual Model: The Process
  • 2.1   An Iterative Approach
  • 2.2   Step 1: Identify Stakeholders
  • 2.3   Step 2: Extract Key Concepts
  • 2.4   Step 3: Use Business Language
  • 2.5   Step 4: Define Entities Clearly
  • 2.6   Step 5: Validate Regularly
  • 2.7   Managing Stakeholder Collaboration
Chapter 3 Key Deliverables
  • 3.1   The Entity Relationship Diagram (ERD)
  • 3.2   The Business Glossary
  • 3.3   The Data Dictionary
Chapter 4 Data Governance: A Modeller's Perspective
  • 4.1   GDPR and the Data Modeller
  • 4.2   Classifying Personal Data
  • 4.3   Encryption and Masking: Practical Examples
  • 4.4   The Modeller's Governance Contributions
  • 4.5   Common Governance Challenges
Chapter 5 The Conceptual Modelling Debate
  • 5.1   Overview of the Debate
  • 5.2   The Case for Conceptual Modelling
  • 5.3   The Graduated View
  • 5.4   The Full Logical Business Model Approach
  • 5.5   Synthesis and Practical Guidance
Chapter 6 The Enterprise Conceptual Data Model
  • 6.1   The Problem
  • 6.2   The Ownership Dispute
  • 6.3   The Proposed Solution: A Two-Tier Ownership Model
  • 6.4   Making the Case to Product Owners
  • 6.5   What Was Not Fully Resolved
  • 6.6   A Practical Path Forward
  • 6.7   Lessons from the Enterprise
Chapter 7 The Human Side of Data Modelling
  • 7.1   Technical Skill Is Necessary but Not Sufficient
  • 7.2   The Stakeholder Access Problem
  • 7.3   The Danger of Agreeing to Unrealistic Targets
  • 7.4   Stakeholder Management and Upward Management Are Equal Skills
  • 7.5   The Human Side Is the Hard Side
  • 7.6   A Reflection for Practitioners
Appendix Quick Reference Card
  • The Align Phase Checklist
  • ERD: What to Include at Conceptual Stage
  • GDPR Data Classification Summary
  • Glossary of Key Terms
Closing Closing Thoughts
  • A final word for practitioners
  • Connect with the author on LinkedIn

Volume 1 of the Data Modelling Series  ·  By Inderjit Thind, MRes (Computer Science), TOGAF Certified

www.linkedin.com/in/inderjit-thind

TABLE OF CONTENTS

Conceptual Data Modelling: A Practitioner's Pocket Handbook  ·  Volume 1

Introduction Foreword
  • About this handbook and how to use it
  • The align, refine, and design framework
Chapter 1 What Is Conceptual Data Modelling?
  • 1.1   Definition and Purpose
  • 1.2   Where Conceptual Modelling Sits in the Lifecycle
  • 1.3   The Align Phase
  • 1.4   What Is and Is Not In Scope
Chapter 2 Building a Conceptual Model: The Process
  • 2.1   An Iterative Approach
  • 2.2   Step 1: Identify Stakeholders
  • 2.3   Step 2: Extract Key Concepts
  • 2.4   Step 3: Use Business Language
  • 2.5   Step 4: Define Entities Clearly
  • 2.6   Step 5: Validate Regularly
  • 2.7   Managing Stakeholder Collaboration
Chapter 3 Key Deliverables
  • 3.1   The Entity Relationship Diagram (ERD)
  • 3.2   The Business Glossary
  • 3.3   The Data Dictionary
Chapter 4 Data Governance: A Modeller's Perspective
  • 4.1   GDPR and the Data Modeller
  • 4.2   Classifying Personal Data
  • 4.3   Encryption and Masking: Practical Examples
  • 4.4   The Modeller's Governance Contributions
  • 4.5   Common Governance Challenges
Chapter 5 The Conceptual Modelling Debate
  • 5.1   Overview of the Debate
  • 5.2   The Case for Conceptual Modelling
  • 5.3   The Graduated View
  • 5.4   The Full Logical Business Model Approach
  • 5.5   Synthesis and Practical Guidance
Chapter 6 The Enterprise Conceptual Data Model
  • 6.1   The Problem
  • 6.2   The Ownership Dispute
  • 6.3   The Proposed Solution: A Two-Tier Ownership Model
  • 6.4   Making the Case to Product Owners
  • 6.5   What Was Not Fully Resolved
  • 6.6   A Practical Path Forward
  • 6.7   Lessons from the Enterprise
Chapter 7 The Human Side of Data Modelling
  • 7.1   Technical Skill Is Necessary but Not Sufficient
  • 7.2   The Stakeholder Access Problem
  • 7.3   The Danger of Agreeing to Unrealistic Targets
  • 7.4   Stakeholder Management and Upward Management Are Equal Skills
  • 7.5   The Human Side Is the Hard Side
  • 7.6   A Reflection for Practitioners
Appendix Quick Reference Card
  • The Align Phase Checklist
  • ERD: What to Include at Conceptual Stage
  • GDPR Data Classification Summary
  • Glossary of Key Terms
Closing Closing Thoughts
  • A final word for practitioners
  • Connect with the author on LinkedIn

Volume 1 of the Data Modelling Series  ·  By Inderjit Thind, MRes (Computer Science), TOGAF Certified

www.linkedin.com/in/inderjit-thind

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