As Netflix's offerings grow, so does the complexity of the systems that support it, leading to duplicated and inconsistent models, inconsistent terminology, data quality issues, and inconsistent relationships between data. To address these challenges, a new foundation is needed to define a model once and reuse those definitions everywhere, connecting concepts to real systems and projecting those definitions outward, generating schemas and enforcing consistency across systems. This led to the development of UDA (Unified Data Architecture), which enables modeling domains once and representing them consistently across systems, powering automation, discoverability, and semantic interoperability. UDA allows users and systems to register and connect domain models, catalog and map domain models to data containers, transpile domain models into schema definition languages, move data faithfully between data containers, discover and explore domain concepts, and programmatically introspect the knowledge graph. UDA is a knowledge graph that connects business concepts to schemas and data containers, grounded in an in-house metamodel called Upper, which defines the language for domain modeling in UDA. Upper is a language for formally describing domains and their concepts, and it is used to model data container representations and mappings. UDA adopts a named-graph-first information model, ensuring resolution, modularity, and governance across the entire graph.