Frequently changing business requirements result not only in changes to the data warehouse (DW) workload but also in changes to the schema structure. These schema changes introduce new DW versions and so the problem of optimization of all of its versions becomes a very challenging one.In this paper we present a new approach for dynamically evolving the design of the implementation schema spanning across its multiple versions. A new derivation procedure for self improvement of the design and the performance of the model is applied in several steps. We also define a system for optimization of the design of the multiversion DW schema and its particular instances and include other factors relevant for optimization of the system i.e. view selection, vertical view fragmentation and index selection. The self improvement of the multiversion schema design is shown by performing large set of experiments.
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