EXTENDING DATA MODELING TO COVER THE WHOLE ENTERPRISE

Data modeling has been valuable for database design. Much research has focused on improving the expressive capabilities of data models [3], on clustering [17] and schema integration [2]. Data modeling techniques [91 have become an integral part of software engineering methodologies [8] and have strongly influenced methods for object-oriented analysis and design [11, 15]. Corporate reality is different, however. In many enterprises, data modeling is applied only on a project-to-project basis and data management struggles to keep track of more than 50,000 data elements accumulated over years. Redundancy factors often exceed 10. In an increasingly complex EDP environment this obstructs information access and seriously impedes software maintenance. These problems have led several companies and the authors to design enterprise-wide data models (EDMs). Some examples drawn from several EDM projects for industry are listed in Table 1. The models #1, #2, #3, #4 and #7 have been developed with assistance of the authors, #5 and #6 are described in [4] and [18].