Approaches to identifying data quality issues: The role of the data broker

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Date
2023-11-06
Authors
Wibisono, Arif
Sammon, David
Heavin, Ciara
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Publisher
Taylor & Francis Group
Published Version
https://doi.org/10.1080/10580530.2023.2274532
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Abstract
Data quality issues are problematic and costly for organizations. Employees (termed “Data Brokers”) must identify data quality issues before data are used for reporting purposes. In five field studies, we investigate how these employees identify these often-hidden data quality issues. Organizations can execute five “checking” approaches: data templates, supervisor validation, data accuracy, data consistency, and data completeness. We discuss each approach, theorize their inter-relationships, and explain their contributions to research and practice.
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Keywords
Data quality issues , Field studies , Data broker , Manual identification , Data curation
Citation
Wibisono, A., Sammon, D. and Heavin, C. (2024) ‘Approaches to identifying data quality issues: the role of the data broker’, Information Systems Management, 41(3), pp. 226–237. Available at: https://doi.org/10.1080/10580530.2023.2274532.
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URI
https://hdl.handle.net/10468/15270
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Cork University Business School - Journal Articles
Copyright
© 2023, Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Information Systems Management on 6 November 2023, available online: https://doi.org/10.1080/10580530.2023.2274532. This material is licensed under a Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0) licence.