A Model Driven Architecture Approach to Generate Multidimensional Schemas of Data Warehouses
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2017, Vol 5, Issue 4
Abstract
Over the past decade, the concept of data warehousing has been widely accepted. The main reason for building data warehouses is to improve the quality of information in order to achieve specific business objectives such as competitive advantage or improved decisionmaking. However, there is no formal method for deriving a multidimensional schema from heterogeneous databases that is recognized as a standard by the OMG and the professionals of the field. Which is why, in this paper, we present a modeldriven approach (MDA) for the design of data warehouses. To apply the MDA approach to the Data warehouse construction process, we describe a multidimensional metamodel and specify a set of transformations from a UML metamodel which is mapped to a multidimensional metamodel. The execution of the transformation, programmed by the Query View Transformation (QVT) language, takes as input an instance of the UML MetaModel to generate an instance of the Dimensional MetaModel as output.
Authors and Affiliations
O. Betari, M. Erramdani, K. Arrhioui
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