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Prof. Dr. S. Decker
RWTH Aachen
Informatik 5
Ahornstr. 55
D-52056 Aachen
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Metadatabase Design for Data Warehouses

Year 2009
Abstract URL view
ISBN-10 0-262-10108-4
ISBN-13 978-0-262-10108-0

Data warehouses (DW) are complex systems which pass massive data from online databases of an enterprise to analysis tools. The analysis tools support the decision making in the enterprise. Obviously, the quality of the decisions depends on the quality of available data with respect to precision, timeliness, completeness, consistency and others). Data warehouses already incorporate meta databases as repositories for the list of available data sources and similar information, but the information is limited to physical and logical aspects of the data warehouse. The approach presented in this chapter makes two major contributions towards a more efficient meta data management in data warehouses. Firstly, we enrich the meta data about DW architectures by using advanced modeling techniques to capture the conceptual knowledge about the information systems. Secondly, we adapt the Goal-Question-Metric approach (GQM) from software quality management to a meta data management environment in order to link special techniques for measuring or optimizing DW quality to a generic conceptual framework of DW quality. The approach has been implemented using the ConceptBase repository system. Thus, ConceptBase serves here as the prototype of a data warehouse meta database that supports the management of meta data and quality information of the data warehouse in a coherent way. The approach has been validated by applying it to the support of specific quality-oriented methods, tools, and application projects in data warehousing. The main lesson learned from this case study is that method engineering can be interlaced with application engineering (data warehouse design) and application use.


In M.A. Jeusfeld, M. Jarke, J. Mylopoulos (eds.): Metamodeling for Method Engineering, MIT Press 2009, pp. 329-355


Published in

Metamodeling for Method Engineering , by M.A. Jeusfeld, M. Jarke, J. Mylopoulos , p. 329-355 ; MIT Press , Cambridge , US .

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