Data Quality and Decision Making

Rosanne Price and Graeme Shanks
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Rosanne Price: Monash University
Graeme Shanks: Monash University

Chapter 4 in Handbook on Decision Support Systems 1, 2008, pp 65-82 from Springer

Abstract: Abstract Decision-makers often rely on data to support their decision-making processes. There is strong evidence, however, that data quality problems are widespread in practice and that reliance on data of poor or uncertain quality leads to less-effective decision-making. Addressing this issue requires first a means of understanding data quality and then techniques both for improving data quality and for improving decision-making based on data quality information. This paper presents a semiotic-based framework for understanding data quality that consists of three categories: syntactic (form), semantic (meaning) and pragmatic (use). This framework is then used as a basis for discussing data quality problems, improvement, and tags, where tags are used to provide data quality information to decisionmakers.

Keywords: Data Quality; Quality Category; Improve Data Quality; Quality Framework; Integrity Rule (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ihichp:978-3-540-48713-5_4

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DOI: 10.1007/978-3-540-48713-5_4

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