The Data Vault Handbook - Concepts and Applications

2.4. MODERN ARCHITECTURES: DATA FABRIC & DATA MESH Data Fabric and Data Mesh are two complementary approaches to modern data architecture, both designed to solve challenges related to scaling, man- aging, and delivering data across complex organizations. Data Fabric is a centralized architecture that integrates and governs data from a variety of sources, such as legacy systems, cloud applications, data lakes, and ware- houses. It provides a unified, secure, and consistent data layer that serves both operational and analytical needs, leveraging technologies like data cat- aloging, orchestration, and governance to ensure data is delivered efficient- ly across the enterprise. While Data Fabric offers a global view of enterprise data, Data Mesh decen- tralizes data management by giving domain-oriented teams the ownership and responsibility for their own data products. The two architectures work in harmony, as Data Fabric can provide the underlying connective tissue that ensures data remains integrated and governed, even as Data Mesh empow- ers different domains to manage and scale their data products independent- ly. This blend of centralized governance (via Data Fabric) and decentralized ownership (via Data Mesh) offers flexibility, scalability, and efficiency in modern data ecosystems. In particular, when we implement a Data Mesh architecture with Data Vault, we should aim for a balance between decentralization and centralization to maximize efficiency and scalability. While it is possible to completely decen- tralize the entire data pipeline, there are significant advantages to keeping certain layers centralized, at least up to the Raw Vault.