The Data Vault Handbook - Concepts and Applications

METHODOLOGY

The methodology in Data Vault will provide us with clear ways of working. Here we will get best practices, frameworks, and guidelines on how to co- ordinate the work and integrate people, processes, and technology. While these standards are rooted in software engineering, they have been updated to meet the needs of modern data projects. Additionally, the methodology extends beyond best practices and coordina- tion strategies to include implementation standards. These standards define how to load data structures and derive information from them, like facts and dimensions. Leveraging the pattern-based nature of the Data Vault model— which relies on metadata—the implementation process itself follows a pat- tern-based approach. This ensures consistency, repeatability, and scalability across the entire data platform. 1.3. GENERAL DEFINITIONS In this guide, we will frequently reference several key concepts related to Data Vault. This section provides brief descriptions of these fundamental terms. 1.3.1. BUSINESS RULES Business rules (also known as soft rules) are logical transformations that we can apply to our data. We call them business rules because these transfor- mations have the goal of adapting the data in a way that serves the business. This could imply cleaning the data, aggregating it, calculating, normalizing or denormalizing, etc. Basically, anything that transforms the data from how it looked from the original source, including its granularity, will be a business rule.