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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Designing a Balanced Data Quality Scorecard

Designing a Balanced Data Quality Scorecard
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Author(s): John Talburt (University of Arkansas at Little Rock, USA) and Traci Campbell (Acxiom Corporation, USA)
Copyright: 2006
Pages: 3
Source title: Emerging Trends and Challenges in Information Technology Management
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-019-6.ch131
ISBN13: 9781616921286
EISBN13: 9781466665361

Abstract

As organizations embrace strategic data quality management, they seek to implement data quality scorecards that display data quality metric results for their information systems. However, defining the metrics that populate these scorecards can be uncharted territory for the organization’s data management team. Negotiations with users over the design of data quality scorecards and scorecard metrics can be facilitated by establishing a common terminology and understanding of dimensions and metric types. This paper presents a classification scheme for metrics and some of the trade-offs related to balancing the composition of a scorecard by types of metrics.

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