Data Vault Cheat Sheet

Data Vault is a data modeling methodology designed for building scalable, flexible, and auditable enterprise data warehouses. Created by Dan Linstedt in the 1990s and formalized as Data Vault 2.0 in 2013, 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. Data Vault 2.1 extends the methodology with enhanced support for semi-structured data, ontologies and taxonomies, and alignment with modern architectures like Data Mesh and Data Lakehouse. Unlike traditional dimensional modeling, Data Vault prioritizes adaptability, compliance, and auditability, making it ideal for environments requiring strict lineage tracking, regulatory compliance, and continuous integration of new data sources.