The text discusses justifying the existence of Data Mesh, a decentralized data architecture. It traces the evolution of data landscape from relational databases to cloud data warehouses, highlighting the limitations of centralized data architecture. The concept of Data Mesh enables data ownership by producers and consumers, relieving the central data team’s burden. It provides references and resources for further reading.
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Justifying the Existence of Data Mesh
Evolution of the Data Landscape
A senior stakeholder at one of my projects mentioned the need to decentralise their data platform architecture and democratise data across the organisation, which left me initially confused. In my journey to understand this concept, I explored the evolution of the data landscape.
During this exploration, I came across the concept of Data Mesh by Zhamak Dehghani, which offers practical solutions to overcome unique challenges in implementing decentralised data architectures. This concept addresses the limitations of centralised data architectures, which can lead to bottlenecks as enterprises grow, making it difficult to gain actionable insights from data.
Decentralised Data Architecture – Data Mesh
Data Mesh is an analytical architecture and operating model that shifts the ownership of analytical data to the teams that most intimately know and own the data—the data producers and consumers. This model aims to alleviate the knowledge burden and delivery pressure on the central data team and enable more efficient data management and insights.
For more information on Data Mesh principles and logical architecture, refer to the following resources:
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