Derived Relations with Exceptions Decision Support Capabilities

Abstract:

Despite the widespread use of relational database management systems, their decision support capabilities have been limited. These limitations include: (1) very limited support for expression of general statements and exceptions, (2) limited capabilities for what-if analysis, and (3) problems with the way derived data is handled. This paper shows that additional power can be placed in relational database systems via a new construct called Derived Relations with Exceptions (dres). Dres are a superset of relational views that provide greater decision support capabilities in that they handle exceptions to general rules and can operate in a hypothetical mode that provides an easier way to experiment with alternative scenarios in a what-if fashion. Dres are implemented by extending the SQL database language.

Key Words and Phrases:

• decision support system
• relational database
• databaseviews
• SQL

Additional information

Notes on contributors

Ronald Datiero

Ronald Dattero is Visiting Assistant Professor of MIS at Louisiana State University. He received his Ph.D. from Purdue University. His research interests are in the areas of decision support systems, database management, artificial intelligence, expert systems, and management science. He is a member of the American Association for Artificial Intelligence, Decision Sciences Institute, Institute of Industrial Engineers, Operations Research Society of America, and The Institute of Management Sciences.

Richard G. Ramirez

Richard G. Ramirez is Assistant Professor of Computer Information Systems at Arizona State University. He received his Ph.D. from Texas A&M University. His research interests focus on derived data in databases, model management systems, and decision support systems.

Joobin Choobineh

Joobin Choobineh is Assistant Professor of Information Systems at Texas A&M University. He received his Ph.D. from the University of Arizona. His research interests include conceptual data modeling, application of artificial intelligence techniques to the database design process, expert database systems, office information systems, and integration of databases and mathematical models. His research results have been published in IEEE Transactions on Software Engineering, Database Engineering, Decision Support Systems, and numerous conference proceedings. He is a member of the Association for Computing Machinery, the IEEE Computer Society, the Decision Sciences Institute, and The Institute of Management Sciences.