For me it was this: ”Moreover, there seems to be little justification for adopting a Data Vault model, especially considering the flexibility of the lakehouse architecture.” Pity its about to be published in an O’Reily book. https://learning.oreilly.com/library/view/-/9781098178826/ch02.html

Imagine a dystopian world, where you are not allowed to use Data Vault. How would you solve all the problems in your Data Warehouse?

https://www.rnz.co.nz/news/business/527419/inland-revenue-giving-thousands-of-taxpayers-details-to-social-media-platforms-for-ad-campaigns?fbclid=IwY2xjawFLSwJleHRuA2FlbQIxMAABHfiQoZd2lKNuLPKWDo5IrGSrtYtTKNwWBrS0kfJBtccVTTWP9FPKrjY3zg_aem_jp9YxiznNYVeVO5Oo9wqfA

Do you agree or disagree with Perplexity.ai 's analysis? 1. Ownership and Structure Data Mesh is fundamentally about decentralising data ownership and treating data as a product. In this approach, data is managed by cross-functional, domain-specific teams, each responsible for their own data products. This decentralization aims to eliminate bottlenecks and empower teams to innovate independently. On the other hand, Data Vault is a centralised data modelling methodology designed for building scalable and flexible data warehouses. It organizes data into three core components: Hubs, Links, and Satellites, which help maintain historical tracking and ensure data integrity. 2. Use Cases and Flexibility Data Mesh is best suited for large-scale, domain-diverse organisations that need to democratise data ownership and processing. It promotes agility and adaptability by allowing each domain to manage its data independently, adhering to company-wide standards. Conversely, Data Vault excels in environments with complex, evolving data landscapes. Its modular design allows for easy integration of new systems and changes, making it ideal for companies that require a robust, adaptable data warehousing solution. 3. Governance and Complexity Governance in Data Mesh is federated, meaning that while each domain has autonomy, there are overarching standards to ensure consistency and compliance. This approach can introduce organizational and cultural complexity due to the shift towards decentralization. In contrast, Data Vault focuses on technical governance through its standardized modeling techniques, ensuring data lineage, auditability, and resilience. While Data Vault can be technically complex due to its specific modeling requirements, it provides a structured approach to managing data integration and historical tracking. Agree or disagree? Let us know your point of view Citations: [1] https://atlan.com/data-mesh-vs-data-vault/