An Automatic Schema-Instance Approach for Merging Multidimensional Data Warehouses

TL;DR

This paper presents an automatic method for merging multidimensional data warehouses at both schema and instance levels, addressing limitations of previous approaches by considering hierarchies and fact tables.

Contribution

It introduces algorithms for merging schemas, hierarchies, and facts in star schema data warehouses, enhancing the merging process with automation and comprehensive data handling.

Findings

Algorithms successfully merge schemas, hierarchies, and facts.

Validated approach with synthetic and benchmark datasets.

Improves accuracy and completeness of data warehouse integration.

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.