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Process Mining

Data Science in Action

  • Wil van der Aalst

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Introduction

    1. Front Matter
      Pages 1-2
    2. Wil van der Aalst
      Pages 3-23
    3. Wil van der Aalst
      Pages 25-52
  3. Preliminaries

    1. Front Matter
      Pages 53-54
    2. Wil van der Aalst
      Pages 55-88
    3. Wil van der Aalst
      Pages 89-121
  4. From Event Logs to Process Models

    1. Front Matter
      Pages 123-124
    2. Wil van der Aalst
      Pages 125-162
    3. Wil van der Aalst
      Pages 163-194
    4. Wil van der Aalst
      Pages 195-240
  5. Beyond Process Discovery

    1. Front Matter
      Pages 241-242
    2. Wil van der Aalst
      Pages 243-274
    3. Wil van der Aalst
      Pages 275-300
    4. Wil van der Aalst
      Pages 301-321
  6. Putting Process Mining to Work

    1. Front Matter
      Pages 323-324
    2. Wil van der Aalst
      Pages 325-352
    3. Wil van der Aalst
      Pages 353-385
    4. Wil van der Aalst
      Pages 387-409
    5. Wil van der Aalst
      Pages 411-427
  7. Reflection

    1. Front Matter
      Pages 429-430
    2. Wil van der Aalst
      Pages 431-445
    3. Wil van der Aalst
      Pages 447-452
  8. Back Matter
    Pages 453-467

About this book

Introduction

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.

Keywords

Business Information Systems Business Intelligence Business Process Management Data Mining Workflow Management Data Science Big Data

Authors and affiliations

  • Wil van der Aalst
    • 1
  1. 1.Eindhoven Technical UniversityEindhovenThe Netherlands

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-49851-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2016
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-662-49850-7
  • Online ISBN 978-3-662-49851-4
  • Buy this book on publisher's site
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