ACM Computing Surveys (CSUR)
Multi-dimensional sequential pattern mining
Proceedings of the tenth international conference on Information and knowledge management
Sequence Learning - Paradigms, Algorithms, and Applications
Sequence Learning - Paradigms, Algorithms, and Applications
Changes of Dimension Data in Temporal Data Warehouses
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Towards Quality-Oriented Data Warehouse Usage and Evolution
CAiSE '99 Proceedings of the 11th International Conference on Advanced Information Systems Engineering
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In order to establish a useful data warehouse, it must be correct and consistent. Hence, when selecting the data sources for building the data warehouse, it is essential know exactly about the concept and structure of all possible data sources and the dependencies between them. In a perfect world, this knowledge stems from an integrated, enterprize-wide data model. However, the reality is different and often an explicit model is not available.This paper proposes an approach for identifying data sources for a data warehouse, even without having detailed knowledge about interdependencies of data sources. Furthermore, we are able to confine the number of potential data sources. Hence, our approach reduces the time needed to build and maintain a data warehouse and it increases the data quality of the data warehouse.