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An Automatic Schema-Instance Approach for Merging Multidimensional Data Warehouses

Databases 2021-07-27 v1

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.

Keywords

Cite

@article{arxiv.2107.12055,
  title  = {An Automatic Schema-Instance Approach for Merging Multidimensional Data Warehouses},
  author = {Yuzhao Yang and Jérôme Darmont and Franck Ravat and Olivier Teste},
  journal= {arXiv preprint arXiv:2107.12055},
  year   = {2021}
}

Comments

25th International Database Engineering & Applications Symposium (IDEAS 2021), Jul 2021, Montreal, Canada

R2 v1 2026-06-24T04:31:09.574Z