The Data Vault Handbook - Concepts and Applications

In this chapter • Learn about modern data platform approaches such as Disciplined Agile and roles definitions, and how they support flexible, scalable, and efficient data managementt • Explore the importance of adopting a product mindset to improve long- term value delivery in Data Vault projects

4. DATA VAULT METHODOLOGY

The Data Vault methodology incorpo- rates various established frameworks,

adapting them for data platform development. These include the Capability Maturity Model Integration (CMMI) for project management, Total Quality Management (TQM) for continuous improvement, Six Sigma for error reduc- tion, and Scrum for team coordination, among others. This guide will not get into each standard in detail, as various resources are available online and in the main Data Vault 2.0 book by Daniel Linstedt and Michael Olschimke (Section 5). Instead, this section focuses on modern approaches to data platform devel- opment methodologies, which we at Scalefree have seen gain widespread adoption among Data Vault practitioners. These approaches include Dis- ciplined Agile, project vs. product mindset, and related concepts such as the definition of modern roles within a data platform team and the prod- uct-based mindset for long-term value delivery. Before getting started with Disciplined Agile, it’s important for readers to have a foundational understanding of Agile and Scrum methodologies, as Dis- ciplined Agile builds upon and extends many of their core concepts. Familiar- ity with Scrum roles, artifacts, and ceremonies will be assumed throughout this section. If you’re not yet familiar with these concepts, we recommend pausing here and referring to the Resources section (Section 5) for further reading before continuing.