Process mining [electronic resource] : data science in action / Wil van der Aalst.
2016
QA76.9.D343
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Can lend chapters, not whole ebooks
Details
Title
Process mining [electronic resource] : data science in action / Wil van der Aalst.
Author
Aalst, Wil van der, author.
Edition
Second edition.
ISBN
9783662498514 (electronic book)
3662498510 (electronic book)
9783662498507
3662498510 (electronic book)
9783662498507
Published
Heidelberg : Springer, 2016.
Language
English
Description
1 online resource (xix, 467 pages)
Item Number
10.1007/978-3-662-49851-4 doi
Call Number
QA76.9.D343
Dewey Decimal Classification
006.3/12
Summary
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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed April 19, 2016).
Available in Other Form
Print version: 9783662498507
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Table of Contents
Introduction
Preliminaries
From Event Logs to Process Models
Beyond Process Discovery
Putting Process Mining to Work
Reflection
Epilogue.
Preliminaries
From Event Logs to Process Models
Beyond Process Discovery
Putting Process Mining to Work
Reflection
Epilogue.