Enterprise Architecture Analysis for Data Accuracy Assessments

• Published in: 2009 IEEE INTERNATIONAL ENTERPRISE DISTRIBUTED OBJECT COMPUTING CONFERENCE pp. 24 - 33
• Main Authors: Narman, P., Johnson, P., Ekstedt, M., Chenine, M., Konig, J.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-09-2009
• Series: IEEE International Enterprise Distributed Object Computing (EDOC) Conference
• Subjects: Accuracy; Application software; Bayesian methods; Computer architecture; Computer industry; Data analysis; Data Quality; Distributed computing; Electrical equipment industry; Enterprise Architecture; Industrial engineering and economy; Industriell teknik och ekonomi; Information analysis; Information technology; Informationsteknik; Software systems; TECHNOLOGY; TEKNIKVETENSKAP; Unified modeling language
• ISBN: 0769537855; 9780769537856
• ISSN: 1541-7719
• DOI: 10.1109/EDOC.2009.26

Poor data in information systems impede the quality of decision-making in many modern organizations. Manual business process activities and application services are never executed flawlessly which results in steadily deteriorating data accuracy, the further away from the source the data gets, the poorer its accuracy becomes. This paper proposes an architecture analysis method based on Bayesian Networks to assess data accuracy deterioration in a quantitative manner. The method is model-based and uses the ArchiMate language to model business processes and the way in which data objects are transformed by various operations. A case study at a Swedish utility demonstrates the approach.