Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/EDOC.2009.26 | EDOC |
Keywords | Field | DocType |
model business process,data accuracy assessment,bayesian networks,swedish utility,archimate language,poor data,data accuracy,enterprise architecture analysis,manual business process activity,data object,architecture analysis method,data accuracy assessments,data accuracy deterioration,data integrity,business process,business,computer architecture,accuracy,bayesian network,information system,enterprise architecture,unified modeling language,information systems,computer and information science,data quality,data analysis,data models,bayesian methods | Information system,Data science,Data mining,Data modeling,ArchiMate,Data architecture,Data quality,Systems engineering,Computer science,Enterprise architecture,Business process,Software engineering,Data integrity | Conference |
ISSN | Citations | PageRank |
2325-6354 | 11 | 0.65 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Per Närman | 1 | 300 | 16.08 |
| Pontus Johnson | 2 | 788 | 55.88 |
| Mathias Ekstedt | 3 | 634 | 49.70 |
| Moustafa Chenine | 4 | 50 | 3.68 |
| Johan König | 5 | 84 | 5.37 |