Process Mining for Data-Driven Business Improvement

Organizations today generate massive amounts of event data, yet many struggle to understand how their business processes actually function in reality. This course bridges the gap between traditional process modeling and modern data science, enabling you to extract objective insights from raw data to streamline operations. You will gain the skills to transform event logs into clear process maps, identifying where bottlenecks occur and where reality deviates from the intended design. By the end of the course, you will be able to apply evidence-based analysis to improve efficiency and support strategic decision-making in any business environment. What you'll learn: - Understand the foundational concepts of event logs, cases, and activities - Discover actual process models from raw data without relying on manual interviews - Perform conformance checking to identify deviations between planned and actual workflows - Apply process enhancement techniques to improve resource allocation and remove bottlenecks - Explore the role of predictive process monitoring and AI-driven discovery in modern analysis - Practice interpreting data patterns to support objective, evidence-based process changes The course begins with essential terminology and the core principles of process science before progressing through techniques for discovery, validation, and optimization using written explanations and practical scenarios. It is designed for beginners in data science or business analysis, requiring no prior experience with specialized modeling software or programming. Start transforming raw event data into clear process insights today.