Next-Cut: a second generation framework for concurrent engineering
Proceedings of the MIT-JSME workshop on Computer-aided cooperative product development
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Efficient intensional redefinition of aggregation hierarchies in multidimensional databases
Proceedings of the 4th ACM international workshop on Data warehousing and OLAP
A multidimensional and multiversion structure for OLAP applications
Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP
Automated data warehousing for rule-based CRM systems
ADC '03 Proceedings of the 14th Australasian database conference - Volume 17
Creation and management of versions in multiversion data warehouse
Proceedings of the 2004 ACM symposium on Applied computing
On querying versions of multiversion data warehouse
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
A user-driven data warehouse evolution approach for concurrent personalized analysis needs
Integrated Computer-Aided Engineering
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A data warehouse is built by collecting data from external sources. Several changes on contents and structures can usually happen on these sources. Therefore, these changes have to be reflected in the data warehouse using schema updating or versioning. However a data warehouse has also to evolve according to new users' analysis needs. In this case, the evolution is rather driven by knowledge than by data. In this paper, we propose a Rule-based Data Warehouse (R-DW) model, in which rules enable the integration of users' knowledge in the data warehouse. The R-DW model is composed of two parts: one fixed part that contains a fact table related to its first level dimensions, and a second evolving part, defined by means of rules. These rules are used to dynamically create dimension hierarchies, allowing the analysis contexts evolution, according to an automatic and concurrent way. Our proposal provides flexibility to data warehouse's evolution by increasing users' interaction with the decision support system.