Process Mining

This comprehensive guide explores process mining, covering topics from data science to predictive analytics. It includes practical applications, tools, and addresses key challenges, making it suitable for analysts and researchers alike.

Process Mining by Wil van der Aalst is a comprehensive exploration of the field of process mining, now presented in its second edition. This updated version places process mining within the broader context of data science and big data methodologies, making it relevant for contemporary applications. The book is structured in a way that begins with a general introduction to data science and process mining, laying a foundational understanding for readers.

In the subsequent sections, the book delves into essential topics such as business process modeling and data mining, which are crucial for grasping the more complex concepts that follow. Part III emphasizes process discovery, regarded as the cornerstone of process mining tasks. Part IV expands on this by examining additional aspects like conformance checking and perspectives related to organization and time. This progression allows readers to appreciate the multifaceted nature of process mining.

The practical application of process mining is addressed in Part V, where the author introduces widely used tools, including the open-source software ProM, alongside various commercial options. Finally, Part VI reflects on the key challenges and insights presented throughout the book, encouraging readers to think critically about the future of process mining. Overall, Process Mining serves as an essential resource for business process analysts, consultants, managers, graduate students, and researchers in the field of business process management.