Abstract
This paper proposes a methodology for automated data base design based on a set of managerial reports. We introduce the notion of report schemata, specified in terms of record types and binary relations, as a framework for analyzing report structures and interactions among reports. Four classes of binary relations are identified, each being characteristic of a certain type of elementary report. Multiple binary relations are used to specify more complex reports. We also discuss concepts such as report covering and the maximal members for transforming reports to a parsimonious representation for data base design. Finally, we formulate this report-driven data base design methodology as an expert consulting system in Artificial Intelligence.
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