Process Mining: Data Science In Action -

: Using data to improve or extend an existing model, such as adding time stamps to predict delays or identifying social networks of resources. Key Takeaways & Learning Path

: Comparing existing process models with actual event data to identify deviations, bottlenecks, or compliance issues. Process Mining: Data Science in Action

, authored by Wil van der Aalst , is the seminal work that bridges the gap between traditional data mining and business process management (BPM). It serves as both a comprehensive academic textbook and the foundation for the popular Coursera course of the same name. Core Framework: The Three Pillars : Using data to improve or extend an

: Automatically learning a process model from raw event data (e.g., using the Alpha-algorithm or Inductive Miner). It serves as both a comprehensive academic textbook

The material is structured to take a learner from data basics to advanced operational support: Process Mining: Data science in Action - Coursera

Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, Wil van der Aalst Data Science in Action Second Edition