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2024 | OriginalPaper | Chapter

7. Insight Through Process Mining

Author : August-Wilhelm Scheer

Published in: The Composable Enterprise: Agile, Flexible, Innovative

Publisher: Springer Fachmedien Wiesbaden

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Abstract

When processes are executed, application systems store data about the start and end of functions in so-called log files. The management and evaluation of these data traces from business processes are referred to as process mining. The structure of log files is described using an example and the essential tasks of process mining such as process model generation and process model comparison are discussed.
Process mining usually refers to the data source log files. But the automatic recording of user activities at the front end also provides data traces for process mining. This task mining is covered at the end of the chapter.
Statements that are very specific or refer to specific systems are marked in italics. Readers who are more interested in an overview can skip these parts without losing the content guide.
The following figure establishes the connection to the lifecycle in Fig. 1.9.

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Footnotes
1
’The ARIS development group at IDS Scheer AG started analysing process instances in the mid‐1990s. Dr Helge Hess and Dr Wolfram Jost played a leading role in the creative ideas. The first process mining system was released for the market by IDS Scheer AG with the product ARIS PPM (Process Performance Manager) in 2000. The first users took it up in the same year and IDS Scheer AG concluded a partnership with SAP AG. Instance processes could be visualised and the actual process model generated. Comparisons between the actual and target model were released 2–3 years later. Software AG has continued to develop the ARIS PPM system since 2009 and still sells it worldwide.
 
2
This was already included in an early version of the product ARIS PPM and was continued in the literature (Ferreira, 2017; van der Aalst, 2011).
 
Literature
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Metadata
Title
Insight Through Process Mining
Author
August-Wilhelm Scheer
Copyright Year
2024
DOI
https://doi.org/10.1007/978-3-658-43089-4_7

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