Data Extraction Foundations for Process Mining

Every successful process mining initiative depends on high-quality data, yet extracting the right event logs is often the most challenging part of the journey. This text-based course demystifies the extraction process, showing you how to locate, capture, and refine transactional data from enterprise databases. You will transition from looking at raw, complex database tables to structuring clean, analysis-ready event logs. What you'll learn: - Understand foundational process mining concepts, including Case IDs, activity names, and timestamps. - Map transactional database schemas to locate process-relevant tables and relationships. - Extract event data using structured SQL queries designed specifically for process reconstruction. - Clean and format raw data to handle missing timestamps, concurrent events, and system noise. - Apply modern data privacy and security principles, including anonymization of sensitive log entries. - Format outputs into standard CSV files and explore modern Object-Centric Event Log (OCEL) structures. Beginning with key terminology and database basics, this course guides you through practical, text-based examples of SQL extraction, data cleansing, and final log validation. It is designed for beginner data analysts, business analysts, and process improvement professionals looking to build their extraction skills from scratch. Start reading today to turn raw database records into clear, actionable process insights.