Data Mesh Principles
- publish-date: 2020-12-03
- author: @zhamak-dehghani
- topics: Data Mesh
Highlights
- data mesh follows a distributed system architecture; a collection of independent data products, with independent lifecycle, built and deployed by likely independent teams.
- However for the majority of use cases, to get value in forms of higher order datasets, insights or machine intelligence there is a need for these independent data products to interoperate; to be able to correlate them, create unions, find intersections, or perform other graphs or set operations on them at scale.
- For any of these operations to be possible, a data mesh implementation requires a governance model that embraces decentralization and domain self-sovereignty, interoperability through global standardization, a dynamic topology and most importantly automated execution of decisions by the platform.
- However for the majority of use cases, to get value in forms of higher order datasets, insights or machine intelligence there is a need for these independent data products to interoperate; to be able to correlate them, create unions, find intersections, or perform other graphs or set operations on them at scale.
federated computational governance
- global standards, local decisions
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