The principles of data mesh are a set of guiding concepts that aim to transform traditional centralized data architectures into decentralized, domain-oriented data platforms.

These principles are designed to address the challenges of managing and scaling data in modern organizations, where data is increasingly becoming a critical asset for decision-making and innovation. The first principle of data mesh is domain-oriented decentralization.

This principle advocates for organizing data around business domains rather than technical functions.

By aligning data with the needs of specific business units or domains, organizations can create more flexible and scalable data architectures that are better able to support the diverse needs of different stakeholders. The second principle of data mesh is data as a product.

This principle emphasizes treating data as a valuable product that is created, managed, and consumed by different parts of the organization.

By applying product management principles to data, organizations can ensure that data is high-quality, well-documented, and easily accessible to those who need it. The third principle of data mesh is self-serve data infrastructure.

This principle calls for providing tools and platforms that enable data consumers to access and analyze data without relying on centralized data teams.

By empowering users to self-serve their data needs, organizations can reduce bottlenecks and accelerate the pace of data-driven decision-making. The fourth principle of data mesh is federated governance.

This principle recognizes that data governance is a shared responsibility that requires collaboration across different parts of the organization.

By establishing federated governance structures that involve data producers, consumers, and stewards, organizations can ensure that data is managed in a consistent and compliant manner. Overall, the principles of data mesh represent a paradigm shift in how organizations approach data management.

By embracing domain-oriented decentralization, treating data as a product, enabling self-serve data infrastructure, and implementing federated governance, organizations can build more agile and scalable data architectures that support their business goals and drive innovation.