Abstract
A set of concepts and architectures that lay the foundation for providing users with intelligent analysis and predictions about business process executions is presented. The tools are able to provide users with information about why the quality of a process execution is low, what will be the outcome of a certain process, or how many processes will be started in future. The information is crucial to gain visibility into the process, understand or foresee problems and areas of optimization, and quickly identify solutions. Intelligent analysis and predictions are achieved by applying data mining techniques to process execution data.
| Original language | English |
|---|---|
| Pages (from-to) | 239-273 |
| Number of pages | 35 |
| Journal | Distributed and Parallel Databases |
| Volume | 16 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Nov 2004 |
| Externally published | Yes |
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Keywords
- Business process
- Business process intelligence
- Metrics
- Prediction
- Process analysis
- Star schema
ASJC Scopus subject areas
- Software
- Information Systems
- Hardware and Architecture
- Information Systems and Management
Cite this
A comprehensive and automated approach to intelligent business processes execution analysis. / Castellanos, Malu; Casati, Fabio; Dayal, Umeshwar; Shan, Ming Chien.
In: Distributed and Parallel Databases, Vol. 16, No. 3, 11.2004, p. 239-273.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A comprehensive and automated approach to intelligent business processes execution analysis
AU - Castellanos, Malu
AU - Casati, Fabio
AU - Dayal, Umeshwar
AU - Shan, Ming Chien
PY - 2004/11
Y1 - 2004/11
N2 - A set of concepts and architectures that lay the foundation for providing users with intelligent analysis and predictions about business process executions is presented. The tools are able to provide users with information about why the quality of a process execution is low, what will be the outcome of a certain process, or how many processes will be started in future. The information is crucial to gain visibility into the process, understand or foresee problems and areas of optimization, and quickly identify solutions. Intelligent analysis and predictions are achieved by applying data mining techniques to process execution data.
AB - A set of concepts and architectures that lay the foundation for providing users with intelligent analysis and predictions about business process executions is presented. The tools are able to provide users with information about why the quality of a process execution is low, what will be the outcome of a certain process, or how many processes will be started in future. The information is crucial to gain visibility into the process, understand or foresee problems and areas of optimization, and quickly identify solutions. Intelligent analysis and predictions are achieved by applying data mining techniques to process execution data.
KW - Business process
KW - Business process intelligence
KW - Metrics
KW - Prediction
KW - Process analysis
KW - Star schema
UR - http://www.scopus.com/inward/record.url?scp=3543141793&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=3543141793&partnerID=8YFLogxK
U2 - 10.1023/B:DAPD.0000031635.88567.65
DO - 10.1023/B:DAPD.0000031635.88567.65
M3 - Article
AN - SCOPUS:3543141793
VL - 16
SP - 239
EP - 273
JO - Distributed and Parallel Databases
JF - Distributed and Parallel Databases
SN - 0926-8782
IS - 3
ER -