Towards a Data Quality Framework for Decision Support in a Multidimensional Context

Towards a Data Quality Framework for Decision Support in a Multidimensional Context

Daniel Poeppelmann, Christian Schultewolter
Copyright: © 2012 |Volume: 3 |Issue: 1 |Pages: 13
ISSN: 1947-3591|EISSN: 1947-3605|EISBN13: 9781466611078|DOI: 10.4018/jbir.2012010102
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MLA

Poeppelmann, Daniel, and Christian Schultewolter. "Towards a Data Quality Framework for Decision Support in a Multidimensional Context." IJBIR vol.3, no.1 2012: pp.17-29. http://doi.org/10.4018/jbir.2012010102

APA

Poeppelmann, D. & Schultewolter, C. (2012). Towards a Data Quality Framework for Decision Support in a Multidimensional Context. International Journal of Business Intelligence Research (IJBIR), 3(1), 17-29. http://doi.org/10.4018/jbir.2012010102

Chicago

Poeppelmann, Daniel, and Christian Schultewolter. "Towards a Data Quality Framework for Decision Support in a Multidimensional Context," International Journal of Business Intelligence Research (IJBIR) 3, no.1: 17-29. http://doi.org/10.4018/jbir.2012010102

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Abstract

Data quality is defined as fitness for use; meaning it is strongly influenced by contextual factors. None of the proposed methods for data quality assessment considers the management level and decision process phase as important contextual factors. Each combination of different management levels and decision process phases can be described as the overall context in which data quality is to be assessed and leads to a certain information demand. The information demand can in turn be described by a set of features whose values depend on the overall context. A context-sensitive assessment of data quality should therefore be based on data quality dimensions related with certain features characterizing the information demand and their values. This paper proposes a framework for data quality assessment based on the contextual factors management level and decision process phase which allows a decision maker to relate data quality dimensions to values of features of the information demand. Based on this individual assignment of dimensions, the user can access situation specific information regarding data quality.

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