Using Multidimensional Canonical Partitioning (MCP) as a Supply-Driven Approach for Data Warehouses Design

Apollinaire Bamana Batoure, Kolyang Kolyang, Michel Tchotsoua


Various information systems have been developed for decision support. But, they rely essentially on transactional methods. From data and transactional databases, we proposed a supply-driven approach to design data warehouses. The approach takes as input, a universal relation, applies vertical partitioning by a greedy type heuristic algorithm. Partitions obtained are transformed into dimensions using a matching algorithm. The other elements of the multidimensional annotation are deduced by guidelines, and the data warehouse schema is generated using a multidimensional conceptual pattern. The transformation of those transactional systems into decision support ones aims at facilitating the storage, exploitation and the representation of data using new databases generation technologies.


Data warehouse design approach; multidimensional data schema; relational database; universal relation; vertical partitioning.

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