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An Automatic Schema-Instance Approach for Merging Multidimensional Data Warehouses

Abstract : Using data warehouses to analyse multidimensional data is a significant task in company decision-making.The data warehouse merging process is composed of two steps: matching multidimensional components and then merging them. Current approaches do not take all the particularities of multidimensional data warehouses into account, e.g., only merging schemata, but not instances; or not exploiting hierarchies nor fact tables. Thus, in this paper, we propose an automatic merging approach for star schema-modeled data warehouses that works at both the schema and instance levels. We also provide algorithms for merging hierarchies, dimensions and facts. Eventually, we implement our merging algorithms and validate them with the use of both synthetic and benchmark datasets.
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https://hal.archives-ouvertes.fr/hal-03265061
Contributor : Jérôme Darmont Connect in order to contact the contributor
Submitted on : Friday, July 23, 2021 - 12:11:22 PM
Last modification on : Tuesday, October 19, 2021 - 2:23:38 PM
Long-term archiving on: : Sunday, October 24, 2021 - 6:26:40 PM

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Distributed under a Creative Commons Attribution 4.0 International License

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Yuzhao Yang, Jérôme Darmont, Franck Ravat, Olivier Teste. An Automatic Schema-Instance Approach for Merging Multidimensional Data Warehouses. 25th International Database Engineering & Applications Symposium (IDEAS 2021), Jul 2021, Montreal, Canada. pp.232-241, ⟨10.1145/3472163.3472268⟩. ⟨hal-03265061⟩

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