As you also may have noticed, I’m the organizer of the Data Modeling Meetup Munich and very interested in closing knowledge gaps related to data modeling and data architecture.
Therefore, the following list is intended as a reading list for people who want to get started with or deepen their knowledge about data modeling. And if you’re already very knowledgeable in this area, maybe it motivates you to have a look at one of the classics again ...
British Museum reading room
By Diliff [CC BY-SA], via Wikimedia Commons
General
- Michael Brackett, Data Resource Design (a little abstract at times but with some interesting thoughts about dealing with data in an organization)
- John Carlis, Mastering Data Modeling: A User-Driven Approach (an under-appreciated classic that introduces shapes and The Flow, a structured way of building and improving data models)
- Terry Halpin & Tony Morgan, Information Modeling and Relational Databases (thorough introduction from an ORM perspective)
- Steve Hoberman, Data Modeling Made Simple: A Practical Guide for Business and IT Professionals (very good introduction to data modeling; there are also some more tool-specific books by the same author)
- William Kent, Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World (originally written in the 1970s but still very relevant as a foundational text)
- Graeme Simsion, Data Modeling: Theory and Practice (interesting study about how people approach data modeling and if it is more description or design)
- Graeme Simsion & Graham Witt, Data Modeling Essentials (the classic introduction into data modeling; goes into more depth than its title suggests)
