Data Model Patterns: Conventions of Thought

Learning the basics of a modeling technique is not the same as learning how to use and apply it. To develop a data model of an organization is to gain insights into its nature that do not come easily. Indeed, analysts are often expected to understand subtleties of an organization's structure that may have evaded people who have worked there for years.

Here's help for those analysts who have learned the basics of data modeling (or "entity/relationship modeling") but who need to obtain the insights required to prepare a good model of a real business. Structures common to many types of business are analyzed in areas such as accounting, material requirements planning, process manufacturing, contracts, laboratories, and documents.

Topics

In each chapter, high-level data models are drawn from the following business areas:

* The Enterprise and Its World
* The Things of the Enterprise
* Procedures and Activities
* Contracts
* Accounting
* The Laboratory
* Material Requirements Planning
* Process Manufacturing
* Documents
* Lower-Level Conventions


Review :
." . . one of the practical values of your book is the set of 'ready to use' models for the most typical applications in many industries. . . . You express your ideas in very simple and easy to understand language. This is how I think such books should be written." "occasionally a book comes along that can be considered a classic; that isn't tied to any particular product or version. David Hay's book, Data Model Patterns: Conventions of Thought, is such a book. . . . It should be mandatory reading before starting any major data modeling or application development task. No other author has gone beyond the theoretical methodology of creating a data model to actually present and analyze real-world models that we can use every day. This book is well written and well illustrated with numerous examples of the models discussed. This is a 'must buy' for your professional library." "Hay does an excellent job at extracting the essence of each 'thing' in order to deal with it as more of an abstraction. This results in much simpler and more powerful data models that are less dependent on cosmetic variations. . . . let this book expand your mind and change your way of thinking." "I found the book articulate and well-ordered, which for a subject as abstruse as data modelling is quite some achievement." "If analysts use the well-proven modelling approach described in this book, and implement the results on relational or object database management systems, they should be able to develop highly business-oriented systems quickly." "This is one of the best practical books on database design I've encountered. It's a well-illustrated, readable (not just for eggheads) 268 pages."