Demystifying Data Vault 2.0

Data Vault emerged in the early 2000s as a response to the extensibility limitations of warehouses built using 3NF and star schema (discussed later in the chapter) models. Data Vault overcame these limitations while retaining the strengths of 3NF and star schema architectures by using a methodology especially suited to meet the needs of large enterprises. Around 2013, Data Vault was expanded to accommodate the growing demand for distributed computing and NoSQL databases, giving rise to its current iteration, Data Vault 2.0.

Data Vault uses a pattern-based design methodology to build an auditable and extensible data warehouse. When most people refer to Data Vault, they are referring to the Raw Vault, which consists of Link, Hub, and Satellite tables. Atop the Raw Vault, sits the Business Vault—designed to be a business-centric layer that abstracts the technical complexities of the underlying data sources and uses constructs such as Point-in-Time...