Enterprise architecture analysis for data accuracy assessments

Authors:
Per Närman;Pontus Johnson;Mathias Ekstedt;Moustafa Chenine;Johan König
Affiliations:
Department of Industrial Information and Control Systems, Royal Institute of Technology, Stockholm, Sweden;Department of Industrial Information and Control Systems, Royal Institute of Technology, Stockholm, Sweden;Department of Industrial Information and Control Systems, Royal Institute of Technology, Stockholm, Sweden;Department of Industrial Information and Control Systems, Royal Institute of Technology, Stockholm, Sweden;Department of Industrial Information and Control Systems, Royal Institute of Technology, Stockholm, Sweden
Venue:
EDOC'09 Proceedings of the 13th IEEE international conference on Enterprise Distributed Object Computing
Year:
2009

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Abstract

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.