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Architecture and quality in data warehouses -An extended repository approach Jarke, M.; Jeusfeld, M.A.; Quix, C.; Vassiliadis, P. Published in: Information SystemsPublication date: 1999 Link to publicationCitation for published version (APA): Jarke, M., Jeusfeld, M. A., Quix, C., & Vassiliadis, P. (1999). Architecture and quality in data warehouses -An extended repository approach. Information Systems, 24(3), 229-253. General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research -You may not further distribute the material or use it for any profit-making activity or commercial gain -You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediately and investigate your claim. (1) Informatik V, RWTH Aachen, 52056 Aachen, Germany (2) Infolab, KUB University, Postbus 90153, 5000 LE Tilburg, The Netherlands (3) Computer Science Division, NTUA Athens, Zographou 15773 Athens, Greece $EVWUDFW -Most database researchers have studied data warehouses (DW) in their role as buffers of materialized views, mediating between update-intensive OLTP systems and query-intensive decision support. This neglects the organizational role of data warehousing as a means of centralized information flow control. As a consequence, a large number of quality aspects relevant for data warehousing cannot be expressed with the current DW meta models. This paper makes two contributions towards solving these problems. Firstly, we enrich the meta data about DW architectures by explicit enterprise models. Secondly, many very different mathematical techniques for measuring or optimizing certain aspects of DW quality are being developed. We adapt the Goal-Question-Metric approach from software quality management to a meta data management environment in order to link these special techniques to a generic conceptual framework of DW quality. The approach has been implemented in full on top of the ConceptBase repository system and has undergone some validation by applying it to the support of specific quality-oriented methods, tools, and application projects in data warehousing.
Abstract. Data warehouses are complex systems that have to deliver highly-aggregated, high quality data from heterogeneous sources to decision makers. Due to the dynamic change in the requirements and the environment, data warehouse system rely on meta databases to control their operation and to aid their evolution. In this paper, we present an approach to assess the quality of the data warehouse via a semantically rich model of quality management in a data warehouse. The model allows stakeholders to design abstract quality goals that are translated to executable analysis queries on quality measurements in the data warehouse's meta database. The approach is being implemented using the ConceptBase meta database system.
Contracts between multiple business partners play an increasing role in a global economy where activities along the value chain are executed by independent yet co-operating companies. Information technology to enact a value chain is now being deployed in the form of ERP systems and Web services. However, there is little known how to formally check whether such an enactment is indeed fulfilling the contract between the parties. In this paper, we investigate which parts of a contract can be formalized to be automatically monitored. Our approach not only supports the detection of actual violations but also pro-active detection of imminent contract violations.
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