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Data Mesh Principles and Logical Architecture

Our aspiration to augment and improve every aspect of business and life with data, demands a paradigm shift in how we manage data at scale. While the technology advances of the past decade have addressed the scale of volume of data and data processing compute, they have failed to address scale in other dimensions: changes in the data landscape, proliferation of sources of data, diversity of data use cases and users, and speed of response to change. Data mesh addresses these dimensions, founded in four principles: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a platform, and federated computational governance. Each principle drives a new logical view of the technical architecture and organizational structure. Zhamak Dehghani, director of emerging technologies at Thoughtworks, provides more details on strategy, implementation, and organizational design in her book Beyond a Monolithic Data Lake to a Distributed Data Mesh.