Designing data marts for data warehouses
ACM Transactions on Software Engineering and Methodology (TOSEM)
Exact and inexact methods for selecting views and indexes for OLAP performance improvement
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
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Careful selection of aggregate views and some of their most used indexes to materialize in a data warehouse reduces the warehouse query response time as well as warehouse maintenance cost under some storage space constraint. Data warehouses collect and store large amounts of integrated enterprise data from a number of independent data sources over a long period of time. Warehouse data are used for online analytical processing to assist management in making quick and competitive business decisions. Precomputing and storing summary tables (materialized views) reduces the amount of time needed to recompute these views across several source tables in order to answer complex warehouse queries. A data cube is an elegant way for representing aggregate information in a Warehouse and is an n-dimensional view with 2/sup n/ subviews. The paper presents a uniform technique for selecting the subviews of the data cube and their indexes to materialize in order to produce the best resultant benefit to the system in terms of query response time and maintenance cost while satisfying some storage space constraint.