When I first heard about Data Vault, I was intrigued by how this methodology managed to combine the best aspects of traditional data warehouse approaches, such as Inmon and Kimball models. To understand its essence, let's start with a brief historical context.

The idea of Data Vault was introduced by Dan Linstedt in the late 1990s. At that time, companies were facing increasing complexity and growing volumes of data, making traditional data warehouse architectures less flexible. Classic models, such as Kimball's star schema, were optimized for analytics but often suffered from complexity when making changes. Inmon's normalization-oriented approach provided scalability but was labor-intensive to develop and adapt. Data Vault emerged as a compromise that addresses these issues.

The core idea of Data Vault is to create a flexible, scalable, and change-resistant data model that easily adapts to business changes. The methodology is based on three types of tables:

• Hubs, which store business keys—unique identifiers such as customer or product IDs.

• Links, which capture relationships between keys.

• Satellites, where attributes and their changes are stored.

This structure allows for a clear separation of data by its purpose and ensures precise tracking of data history.

What makes Data Vault particularly attractive? It is an approach focused on flexibility and longevity. For example, in traditional data warehouses, any changes in business logic often require restructuring the entire model. In Data Vault, changes are handled selectively by adding new satellites or links without altering the core structure.

Another significant advantage is auditability and traceability. Every record in Data Vault is accompanied by a timestamp and technical metadata, allowing not only data analysis but also an understanding of where the data came from and how it has changed.

When should you choose Data Vault? If your business faces rapid changes, large volumes of data, and strict transparency and audit requirements, this is one of the best options. Data Vault is especially effective for building Enterprise Data Warehouses (EDWs) that need to be resilient to change.

In the following sections, we will dive into the details so that you can not only understand how Data Vault works but also learn how to apply it in practice.