Airbnb's data classification system identifies and protects personal data, ensuring trust and compliance. The system comprises three pillars: cataloging to locate data, detection to identify personal data, and reconciliation to verify classifications. Automated detection uses metadata, content, and machine learning to classify personal data. Human input confirms classifications to minimize false positives and facilitate resolution. Quality metrics assess recall, precision, and speed to ensure effectiveness. Challenges include post-processing classification, inconsistent classifications, and process costs. Airbnb advocates "shifting left" by integrating data classification into data schemas at creation to address these challenges. This approach empowers data owners to manage and annotate their data, leveraging lineage information for automated annotation and reducing manual effort. Airbnb's data classification system provides a comprehensive framework for organizations facing similar challenges, promoting data protection and compliance.