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.
