Chapter 2. Principle of Domain Ownership

Data mesh, at its core, is founded in decentralization and distribution of data responsibility to people who are closest to the data. This is to support a scale-out structure and continuous and rapid change cycles.

The question is how to identify the boundaries around which the data is decomposed, how to integrate those components, and, consequently, how to distribute the responsibilities.

To find the axis of data decomposition, data mesh follows the seams of organizational units. It follows the lines of division of responsibility aligned with the business. It does not follow the borders set by the underlying technology solutions, such as the lake, warehouse, pipelines, etc., nor the functional lines, data team, or analytics team.

The data mesh approach is contrary to how existing data architectures are partitioned and data responsibility is divided. Chapter 8 demonstrates that traditional data architectures are partitioned around technology, e.g., data warehouses, and give data ownership to teams performing activities related to the technology, e.g., the data warehouse team, data pipeline team, etc. The traditional architectures mirror an organizational structure that centralizes the responsibility of sharing analytical data to a single data team. The previous approaches have been set up to localize the complexity and cost of dealing with a relatively new field of analytical data management within a specialized group.

The past approach ...

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