Analysis and Design of Data Warehouses

With the large-scale introduction of the data warehouse concept, a new phenomenon has appeared in the field of information systems development. Facts in a data warehouse – as opposed to those in an operational database – mainly represent immutable, aggregated or otherwise derived, historical information. The aggregation level and specific layout of management information reports often cannot be specified on beforehand. Therefore, a data warehouse must be designed in such a way, that it provides optimal support for aggregation on the fly and for navigation through aggregation hierarchies, that it allows easy access to time series and that it enables reporting in any desired layout. This publication describes the outline of two complementary methods for the analysis of data warehouse relations; one simple and the other advanced. The simple method exploits the knowledge contained in an ordinary relational schema. The advanced method is based on the analysis of derivation rules. Subsequently, the design of data warehouses based on these methods is investigated. Special attention has been given to the actuality of data warehouses that contain historical information, to the transitivity of derivations, to the navigation through aggregation hierarchies via so-called drill paths and to the maintenance of various aggregation levels within a single data warehouse relation.