Abstract
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. Initial feedback from ongoing experiments with a partial implementation of the resulting meta data structure in three industrial case studies provides a partial validation of the approach.
This research was partially supported by the European Commission in ESPRIT Long Term Research Project DWQ (Foundations of Data Warehouse Quality), by the General Secretariat of Research and Technology (Greece) under the PENED program; and by the Deutsche Forschungsgemeinschaft through Graduiertenkolleg ”Informatik und Technik”.
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Jarke, M., Jeusfeld, M.A., Quix, C., Vassiliadis, P. (1998). Architecture and quality in data warehouses. In: Pernici, B., Thanos, C. (eds) Advanced Information Systems Engineering. CAiSE 1998. Lecture Notes in Computer Science, vol 1413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0054221
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