Applying MDA and universal data models for data warehouse modeling
ACMOS'08 Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation
Semantic enrichment of strategic datacubes
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
Supporting Ontology-Based Dynamic Property and Classification in WebSphere Metadata Server
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
A model-driven goal-oriented requirement engineering approach for data warehouses
ER'07 Proceedings of the 2007 conference on Advances in conceptual modeling: foundations and applications
| Hi-index | 0.00 |
Enterprise organizations use Data Warehouses (DWHs) analyze their performance. Performance is judged regarding the achievement of goals. DWH data models are well established. There exist numerous domain-specific modeling approaches. Enterprises also often model their goals in terms of formal or semiformal goal models. The problem is that these two aspects - the Data Warehouse and the Enterprise Goals - are described separately and not related to each other. We identify a need for combining these two aspects. If their relationship is made explicit, it can be used to enhance the way users access and interpret data in the DWH. To address this limitation, in this paper we introduce a weaving model between enterprise goals and DWH data. Thus we present a domain-specific application of model weaving to an aspect of enterprise computing. We describe metamodels for both aspects as well as the weaving links between them, which allows to show the aspects separately but also in combination. We furthermore illustrate how to use the weaving links to create business metadata. Business metadata can be used in the DWH to describe the business context and implications of the data to the users, but is usually not available in today's DWHs. We apply our approach to a sample situation, which is used as a running example in the paper.