Process Mining Fundamentals: Analyzing Business Processes with Event Logs

In modern organizations, business operations generate vast amounts of data stored across transactional event logs. Understanding this data is essential for identifying operational bottlenecks, reducing costs, and improving workflow efficiency. This comprehensive text course provides a structured introduction to process mining, bridging the gap between data science and business process management. You will start with foundational terminology, core definitions, and key concepts, learning how event logs record case identifiers, activity names, and timestamps. From there, you will explore process discovery techniques, performance analysis, conformance checking, and practical process enhancement methods. What you'll learn: Understand core process mining principles, event log structures, and standard formats. Discover business workflows automatically using foundational process discovery algorithms. Analyze operational bottlenecks and execution delays from structured process data. Perform conformance checking to compare actual business execution against reference models. Apply data cleaning and preprocessing methods to handle real-world event data using Python libraries like PM4Py. Evaluate process enhancement strategies to optimize organizational workflows. The course guides you step-by-step from essential concepts and data formats through to analytical workflows and practical process evaluation. Designed for beginners, business analysts, process owners, and entry-level data specialists, no prior background in process analytics is required. Begin reading today to build practical skills in process analytics and data-driven workflow optimization.