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Data Mesh: Data-Driven Value at Scale • Zhamak Dehghani & Samia Rahman
Data Mesh is a new approach to data management that enables decentralization, autonomy, and domain-oriented ownership for data-driven value at scale, featuring principles of collaboration and data product thinking.
- Data Mesh is a new approach to data management that focuses on decentralization and autonomy of data organizations.
- The traditional data management approach is no longer suitable for the complexity of modern data.
- Data Mesh establishes a new way of governing data, driven by principles of domain-oriented ownership and collaboration.
- The four principles of Data Mesh are: 1) domain-oriented ownership, 2) decentralized governance, 3) data as a product, and 4) decentralized data management.
- Data Mesh encourages data sharing and reuse, but also requires clear ownership and governance.
- The approach is often misunderstood, and requires a fundamental shift in how organizations think about data.
- Data catalogs and centralized approaches are not the solution, as they can lead to redundancy and inefficiency.
- Instead, Data Mesh advocates for a decentralized approach, where each domain is responsible for its own data.
- The approach can be applied to any domain, but requires a deep understanding of the business and the data.
- The book “Data Mesh” aims to provide a comprehensive guide to implementing Data Mesh, with practical advice and real-world examples.
- The book covers foundational concepts, as well as best practices and case studies.
- The author uses a visual language to explain complex concepts, making it more accessible to a wider audience.
- The book is aimed at a wide range of readers, including data analysts, data scientists, data engineers, and business leaders.
- The author emphasizes the importance of understanding the business and the data before implementing Data Mesh.
- The book provides guidance on how to identify the best domains to start with, and how to prioritize initiatives.