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Data Science in Action Chapter Apr 2016 Process Mining pp.3-23 In recent years, data science emerged as a new and important discipline. It can be viewed as an amalgamation of.


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Process Mining: Data Science in ActionApril 2016 Author: Wil van der Aalst Publisher: Springer Publishing Company, Incorporated ISBN: 978-3-662-49850-7 Published: 16 April 2016 Pages: 467 Available at Amazon Save to Binder Export Citation Bibliometrics Downloads (cumulative) 0 Citation count 81 Downloads (6 weeks) 0 Downloads (12 months) 0


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Process Mining: Data Science in Action About the 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.. After a general introduction to data science and process mining in Part I, Part II provides the basics of.


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Process Mining: Data science in Action Taught in English 19 languages available Some content may not be translated Enroll for Free Starts Jan 5 Financial aid available 83,045 already enrolled Course Gain insight into a topic and learn the fundamentals Instructor: Wil van der Aalst Included with Coursera Plus 4.7 (1,176 reviews) Intermediate level


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Process Mining Data Science in Action Home Book Authors: Wil van der Aalst 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


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Process Mining: Data Science in ActionMay 2018 Author: Wil M. P. Van Der Aalst Publisher: Springer Publishing Company, Incorporated ISBN: 978-3-662-57041-8 Published: 10 May 2018 Pages: 488 Available at Amazon Save to Binder Export Citation Bibliometrics Downloads (cumulative) 0 Citation count 0 Downloads (6 weeks) 0 Downloads (12 months) 0


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Description Creators/Contributors Author/Creator Aalst, Wil van der, author. Contents/Summary Bibliography Includes bibliographical references and index. Contents Introduction Preliminaries From Event Logs to Process Models Beyond Process Discovery Putting Process Mining to Work Reflection Epilogue.


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Process Mining: Data science in Action Created by: Wil. van der Aalst The course explains the key analysis techniques in process mining. Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data.


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Process Mining: Data Science in Action 2nd Edition, Kindle Edition by Wil M. P. van der Aalst (Author) Format: Kindle Edition 4.6 49 ratings


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About this course: Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains.


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Learn more about the Process Mining: Data science in Action course here including a course overview, cost information, related jobs and more.


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Paperback. $39.39 5 Used from $49.70 16 New from $39.39. 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.


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Process Mining is a new kind of Business Analytics and has emerged as a powerful family of Process Science techniques for analysing and improving business processes.


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Process Mining: Data Science in Action. Hardcover - 26 April 2016. 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.


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Wil M. P. van der Aalst Springer Berlin Heidelberg, Apr 26, 2016 - Computers - 467 pages This is the second edition of Wil van der Aalst's seminal book on process mining, which now discusses.


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Process Mining in Action describes principles, challenges and learnings from years of practice." (Seungjin Whang, Professor of Operations, Information & Technology at Stanford Graduate School of Business) "This is a timely book that presents operational experiences and brings Process Mining application problems to academic research communities.