Data Vault is a data modeling methodology designed for building scalable, flexible, and auditable enterprise data warehouses. Invented by Dan Linstedt in the 1990s and published in 2000, Data Vault addresses the challenges of managing complex, rapidly changing data from multiple sources while maintaining complete historical accuracy and auditability. The methodology separates business keys, relationships, and descriptive attributes into distinct table types—Hubs, Links, and Satellites—enabling parallel loading, incremental development, and minimal impact from source system changes. Unlike traditional dimensional modeling, Data Vault prioritizes adaptability and compliance over query performance, making it ideal for environments requiring strict lineage tracking, regulatory compliance, and continuous integration of new data sources.