CONCLUSION

In this chapter we have argued that dimensions in a data warehouse are not static entities, but are subject to updates, either at the schema or instance level. We presented a temporal multidimensional model, and a query language supporting it which we denoted TOLAP. TOLAP accounts for schema versioning, allowing expressing complex queries at a high abstraction level. We also show a first implementation of the temporal model.

TOLAP can be extended in order to allow the definition of constraints, which could be easily introduced within our visualization tool. Also, there is space for studying query optimization in TOLAP. Another issue which deserves attention is adding update support to TOLAP, allowing bulk updates like "delete all customers who had not completed any transaction since 1998." Also, transactions and update expressions in TOLAP must be addressed. For example, the expression above could be followed by: "classify all customers who did not perform any transaction since 1999 as ‘low-priority’ customers."

A second version of TOLAP is currently under construction. It will provide a totally platform-independent system, with a three-tier architecture. A front-end web-enabled application will communicate with an application server, in which XML metadata will be stored. The back end will be any database management system where the data warehouse will be stored.



Multidimensional Databases(c) Problems and Solutions
Multidimensional Databases: Problems and Solutions
ISBN: 1591400538
EAN: 2147483647
Year: 2003
Pages: 150

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