5 Must-Read Database Modeling Books?

I recently realized that our database modeling library could use a few more advanced titles. So I headed over to Amazon to see what they had on offer.

There are plenty of introductory books for beginners that tell you how to normalize data, and introduce you to indexes, but what about something for the professional, grown-up database modeler? Here are 5 of the best database modeling books I found (listed in no particular order) that go beyond the basics and come highly recommended by Amazon reviewers. Go ahead and add them to your wishlists!

1. The Data Model Resource Book is actually a series of three books by Len Silverston, a data modeling consultant, speaker at conferences, and founder of Universal Data Models. The last book in the series is co-authored with Paul Agnew, Len Silverston’s co-worker. The books are compared to the famous “gang of four” pattern books in object-oriented programming.
   
   

   	The Data Model Resource Book Volume 1: A Library of Universal Data Models for All Enterprises. The book contains a collection of data modeling patterns. The topics include handling roles, hierarchies, contacts, classification and others.
   	The Data Model Resource Book Volume 2: A Library of Data Models for Specific Industries. In the book the templates are organized by industry. There are separate chapters for Manufacturing, Telecommunications, Health Care, Insurance, Financial Services, Professional Services, Travel, and E-Commerce models.
   	The Data Model Resource Book Volume 3: Universal Patterns for Data Modeling. From the table of contents alone, this book seems similar to Volume 1 so I'm not sure how this book compares to book 1.

   
   

   The primary complaints about these books revolve around the lack of complete SQL scripts for the models provided. The SQL scripts can be purchased separately on a CD.

   
   
2. Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World by William Kent.
   
   

   This book was first published in 1978 (when relational databases had just been invented). The third edition was updated by Steve Hoberman who also added commentary throughout the book. This book is so old that it should have been marked as obsolete. Yet the Amazon reviews are stellar:

   • “If you are in data modeling and database area, believe me, this is a must read.”
   • “This short book is a combination of practical data modeling thinking and the broader topic of information within database systems.”
   • “Anyone in the field of data including data architects, designers and developers should read this book and internalize the concepts and issues identified in it. Only then will you have a “real” perspective on data.“
   I understand that the book is more about the philosophy of data rather than an actual data modeling book. However, an almost 40-year-old book on computer science that is still being recommended must be an interesting read.
   
   
3. Data Model Patterns: A Metadata Map by David C. Hay.
   
   The author, David C. Hay is a data modeling consultant, and the founder of consulting company Essential Strategies, Inc.. He is also the author of many data modeling books.
   This book is based on the Zachman Framework, a formal and structured way of viewing an enterprise. The framework is a two-dimensional matrix, usually a 6x6 matrix. The columns focus on fundamental questions: what (data), how (activities), where (locations), who (people), when (timing), and why (motivation). The rows correspond to various perspectives: Business Owner’s perspective, the Architect’s perspective, the Designer’s perspective, and others. The Amazon reviews claim that the Zachman framework is described better here than in the articles by Zachman himself. The author uses his practical experience in data modeling in various industries to provide a step-by-step guide on enterprise information management. Because the book is based on the Zachman framework, it is organized so that different readers can benefit from different parts.
   
   
4. Data Model Patterns: Conventions of Thought by David C. Hay.
   
   A previous book by David C. Hay. It is available as an eBook which is a digital version of the printed book from 1996. This book seems to be more down-to-earth than A Metadata Map.
   The book is about applying data modeling rules in the enterprise world. It analyzes structures common to many types of business. In each chapter, high-level data models are given for business areas like Procedures and Activities, Contracts, Accounting, Material Requirements Planning, Documents and others.
   
   
5. The DAMA Guide to the Data Management. Body of Knowledge
   
   DAMA International is a professional association for data modelers, analysts, and information resource managers. The organization aims to promote the understanding, development and practice of managing information. The book is a compilation of data management best practices. It tries to set up standards for data management.
   I have seen some comments that the book is becoming out-of-date as it does not handle big-data issues. As far as I know, the revised second edition is on its way. Hopefully, the new edition will handle big data too.
   
   

Which of these books would you recommend? Do you know any other database modeling books worth reading?