Table of Contents
Practical Data Modeling Book - TOC
The following is the table of contents for Practical Data Modeling (working title), my new book. It is likely to evolve as I write it. As new chapters are added, they’ll be linked here so you can quickly find what you’re looking for.
Please note that reading these chapters requires a Practical Data Modeling subscription. This is because I’m a solo writer, and writing helps me earn a living. If you’re a subscriber, you’ll get a free digital version of the final book. I’ll also send out some signed physical copies to some lucky people. You’ll also get access to exclusive community discussions and events, discounts on workshops and training, and much more. Thanks so much for your support!
The final book will be available as a physical paperback (possibly hardcover), digital download, and audiobook. I expect the book to be published sometime in H1 2025, with an audiobook and course coming shortly after.
The final digital version on Substack will contain videos and other materials to supplement your learning.
Note that dates provided in the TOC are estimates, and likely to change due to challenges of research, writing, editing, and life in general.
Thanks,
Joe Reis1
Part 1 - Mixed Model Arts
Chapter 1 - What is (and isn’t) Data Modeling?
Chapter 2 - What is this all for?
Chapter 3 - Brief History Lessons and Mixed Model Arts
Part 2 - Data Modeling Building Blocks
Chapter 4 - The Major Forms of Data
Chapter 5 - Entities
Chapter 6 - Attributes
Chapter 7 - Relationships
Chapter 8 - Grains
Chapter 9 - Mapping the Model
Subject Areas
Business Processes
Domains
Chapter 10 - Levels of Modeling
Conceptual
Logical
Physical
Part 3 - Building a Data Model
Chapter 11 - Building and Maintaining a Data Model
Chapter 12 - Application Data Modeling
Relational
NoSQL
Events
Streaming
Other
Chapter 13 - Analytical Data Modeling
Kimball
Data Vault
One Big Table
Streaming
Other
Chapter 14 - Machine Learning and AI Data Modeling
Structured Data
Unstructured Data
Other
Part 4 - The Other Important Stuff
Chapter 15 - Architecture and Systems
Chapter 16 - People and Organizations
Chapter 17 - The Future of Data Modeling
Chapter 18 - Conclusion
Plus, there are bonus chapters and articles for paying subscribers!
updated 10/312024
What are the thoughts on like, examples of different data modelling techniques? Feels like going into the intricacies of something like Data Vault, for example, would be out of scope (fair) but an example or high level explanation might be cool (with examples).
And perhaps a section on what *not* to do ("How to avoid chaos"). Otherwise can't wait
How to buy this book?