Overview
- First book on process mining, bridging the gap between business process modeling and business intelligence and positioning process mining within the rapidly growing data science discipline
- This second edition includes over 150 pages of new material, e.g. on data quality, the relation to data science, inductive mining techniques and the notion of alignments
- Written by one of the most influential and most-cited computer scientists and the best-known BPM researcher
- Self-contained and comprehensive overview for a broad audience in academia and industry, including up-to-date information on tools and the exploitation of modern IT infrastructures
- Includes supplementary material: sn.pub/extras
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Table of contents (16 chapters)
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Front Matter
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Introduction
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Front Matter
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Preliminaries
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Front Matter
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From Event Logs to Process Models
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Front Matter
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Beyond Process Discovery
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Front Matter
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Putting Process Mining to Work
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Front Matter
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Keywords
About this book
This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics.
After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges.
Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.
Reviews
Authors and Affiliations
About the author
Wil van der Aalst is a full professor at the Department of Mathematics & Computer Science of the Technische Universiteit Eindhoven (TU/e), The Netherlands, where he chairs the Architecture of Information Systems (AIS) group and serves as the scientific director of the Data Science Center Eindhoven. He also has a part-time appointment in the BPM group of Queensland University of Technology (QUT), Australia. His research and teaching interests include information systems, business process management, process modeling, Petri nets, process mining, and simulation.
Wil has published more than 180 journal papers, 19 books, 425 refereed conference or workshop publications, and 60 book chapters. Many of his papers are highly cited (he has a H-index of more than 123 according to Google Scholar, the highest among all European computer scientists) and his ideas on process support have influenced researchers, software developers, and standardization committees worldwide.
Bibliographic Information
Book Title: Process Mining
Book Subtitle: Data Science in Action
Authors: Wil van der Aalst
DOI: https://doi.org/10.1007/978-3-662-49851-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2016
Hardcover ISBN: 978-3-662-49850-7Published: 26 April 2016
Softcover ISBN: 978-3-662-57041-8Published: 22 April 2018
eBook ISBN: 978-3-662-49851-4Published: 15 April 2016
Edition Number: 2
Number of Pages: XIX, 467
Number of Illustrations: 237 b/w illustrations, 13 illustrations in colour
Topics: Information Systems Applications (incl. Internet), Information Storage and Retrieval, IT in Business, Software Engineering, Logics and Meanings of Programs, Computer Appl. in Administrative Data Processing