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Multilevel business processes = modeling and data analysis /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Multilevel business processes/ by Christoph G. Schuetz.
Reminder of title:
modeling and data analysis /
Author:
Schuetz, Christoph G.
Published:
Wiesbaden :Springer Fachmedien Wiesbaden : : 2015.,
Description:
xxiv, 232 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Management information systems. -
Online resource:
http://dx.doi.org/10.1007/978-3-658-11084-0
ISBN:
9783658110840
Multilevel business processes = modeling and data analysis /
Schuetz, Christoph G.
Multilevel business processes
modeling and data analysis /[electronic resource] :by Christoph G. Schuetz. - Wiesbaden :Springer Fachmedien Wiesbaden :2015. - xxiv, 232 p. :ill., digital ;24 cm.
Core Metamodel for Multilevel Objects -- Multilevel Business Artifacts -- Hetero-Homogeneous Business Process Models -- Multilevel Business Process Automation -- Multilevel Business Process Intelligence.
Christoph G. Schuetz examines the conceptual modeling aspects of multilevel business processes without neglecting the implementation aspects. Furthermore, he investigates the advantages of hetero-homogeneous models for quantitative business process analysis. Multilevel models reflect the reality of many information systems. In this respect process-aware information systems are no exception. Multilevel models capture interdependencies between business processes at different organizational levels and allow for a convenient representation of business process variability which, in turn, facilitates the analysis of business processes across different organizational units. Contents Core Metamodel for Multilevel Objects Multilevel Business Artifacts Hetero-Homogeneous Business Process Models Multilevel Business Process Automation Multilevel Business Process Intelligence Target Groups Researchers and students in business informatics, computer science, and business administration. Business process management professionals The Author Christoph G. Schuetz is a postdoctoral researcher at the Department of Business Informatics - Data & Knowledge Engineering of the Johannes Kepler University Linz, Austria. His research interests include data warehousing, semantic web, business process management, and data privacy.
ISBN: 9783658110840
Standard No.: 10.1007/978-3-658-11084-0doiSubjects--Topical Terms:
561123
Management information systems.
LC Class. No.: HD30.2 / .S38 2015
Dewey Class. No.: 658.4034
Multilevel business processes = modeling and data analysis /
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Core Metamodel for Multilevel Objects -- Multilevel Business Artifacts -- Hetero-Homogeneous Business Process Models -- Multilevel Business Process Automation -- Multilevel Business Process Intelligence.
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Christoph G. Schuetz examines the conceptual modeling aspects of multilevel business processes without neglecting the implementation aspects. Furthermore, he investigates the advantages of hetero-homogeneous models for quantitative business process analysis. Multilevel models reflect the reality of many information systems. In this respect process-aware information systems are no exception. Multilevel models capture interdependencies between business processes at different organizational levels and allow for a convenient representation of business process variability which, in turn, facilitates the analysis of business processes across different organizational units. Contents Core Metamodel for Multilevel Objects Multilevel Business Artifacts Hetero-Homogeneous Business Process Models Multilevel Business Process Automation Multilevel Business Process Intelligence Target Groups Researchers and students in business informatics, computer science, and business administration. Business process management professionals The Author Christoph G. Schuetz is a postdoctoral researcher at the Department of Business Informatics - Data & Knowledge Engineering of the Johannes Kepler University Linz, Austria. His research interests include data warehousing, semantic web, business process management, and data privacy.
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