We show three interrelated tools intended to improve different aspects of the quality of data warehouse solutions. Firstly, the deductive object manager ConceptBase is intended to enrich the semantics of data warehouse solutions by including an explicit enterprise-centered concept of quality. The positive impact of precise multidimensional data models on the client interface is demonstrated by CoDecide, an Internet-based toolkit for the flexible visualization of multiple, interrelated data cubes. Finally, MIDAS is a hybrid data mining system which analyses multi-dimensional data to further enrich the semantics of the meta database, using a combination of neural network techniques, fuzzy logic and machine learning.

CoDecide is an experimental user interface toolkit that offers an extension to spreadsheet concepts specifically geared towards support for cooperative analysis of the kinds of multi-dimensional data encountered in data warehousing. It is distinguished from previous proposals by direct support for drill-down/roll-up analysis without redesign of an interface; more importantly, CoDecide can link multiple views on a data cube for synchronous or asynchronoous cooperation by multiple analysts, through a conceptual model visualizing the problem dimensions on so-called tapes. Tapes generalize the ideas of ranging and pivoting in current data warehouses for the multi-perspective and multi-user case. CoDecide allows the rapid composition of multi-matrix interfaces and their linkage to underlying data sources. A LAN version of CoDecide has been used in a number of design decision support applications. A WWW version representing externally materialized views on databases is currently under development.