LOGICAL DATA MODELING: What It Is and How To Do IT is directed toward three groups of people: (1) Business subject matter experts, (2) information technology professionals, (3) advanced students in Computer Science, Management Information Systems, and e-Business. Its purpose is to outline the basics of logical data modeling-specifically, data modeling for relational database management systems-in simple, practical terms and in a business context. The focus on relational data modeling is consciously made because it is superior in modeling real business activities.

By reading and understanding this book, the enterprise-side project managers should gain enough understanding of data modeling to understand the principles and help communicate that understanding to the people who know the business, do the work, and are going to be affected by the system that is being created.

Résumé

Logical Data Modeling offers business managers, analysts, and students a clear, basic systematic guide to defining business information structures in relational database terms. The approach, based on Clive Finkelstein's business-side Information Engineering, is hands-on, practical, and explicit in terminology and reasoning. Filled with illustrations, examples, and exercises, Logical Data Modeling makes its subject accessible to readers with only a limited knowledge of database systems. The book covers all essential topics thoroughly but succinctly: entities, associations, attributes, keys and inheritance, valid and invalid structures, and normalization. It also emphasizes communication with business and database specialists, documentation, and the use of Visible Systems' Visible Advantage enterprise modeling tool. The application of design patterns to logical data modeling provides practitioners with a practical tool for fast development. At the end, a chapter covers the issues that arise when the logical data model is translated into the design for a physical database.

Contenu
Getting Started.- The Art Gallery Web: A Data Modeling Example.- Building the Data Map.- The Art Gallery Web (Continued).- Keys and Valid Associations.- The Art Gallery Web (Continued).- Defining Attributes.- The Art Gallery Web (Continued).- Verifying the Data Model.- Validating the Data Model.- Design Patterns.- From Logical to Physical.- The End and the Beginning.