Title: Data quality assessment and improvement

Authors: Risto Silvola; Janne Harkonen; Olli Vilppola; Hanna Kropsu-Vehkapera; Harri Haapasalo

Addresses: Industrial Engineering and Management, University of Oulu, Finland P.O. Box 4610, FI-90014, Finland ' Industrial Engineering and Management, University of Oulu, Finland P.O. Box 4610, FI-90014, Finland ' Industrial Engineering and Management, University of Oulu, Finland P.O. Box 4610, FI-90014, Finland ' Industrial Engineering and Management, University of Oulu, Finland P.O. Box 4610, FI-90014, Finland ' Industrial Engineering and Management, University of Oulu, Finland P.O. Box 4610, FI-90014, Finland

Abstract: Data quality has significance to companies, but is an issue that can be challenging to approach and operationalise. This study focuses on data quality from the perspective of operationalisation by analysing the practices of a company that is a world leader in its business. A model is proposed for managing data quality to enable evaluation and operationalisation. The results indicate that data quality is best ensured when organisation specific aspects are taken into account. The model acknowledges the needs of different data domains, particularly those that have master data characteristics. The proposed model can provide a starting point for operationalising data quality assessment and improvement. The consequent appreciation of data quality improves data maintenance processes, IT solutions, data quality and relevant expertise, all of which form the basis for handling the origins of products.

Keywords: data quality assessment; data quality improvement; operationalisation; master data; product data management; PDM; information systems; dimensions; operations; data quality management; data maintenance.

DOI: 10.1504/IJBIS.2016.075718

International Journal of Business Information Systems, 2016 Vol.22 No.1, pp.62 - 81

Received: 26 Oct 2014
Accepted: 17 Dec 2014
Published online: 01 Apr 2016 *

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