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.
