Data Mesh architecture implementation on Azure data lake

Question

Hi friends, Data mesh architecture is a decentralized approach that organizes data based on business domains (e.g., marketing, sales, HR), I have the following questions

• Is it required to build a separate data lake for each department?
• When data needs to be viewed as a consolidated form, how does the integration happen, and how does the architecture approach this consolidation?
• Each department is supposed to have its own governance and security rules What are the challenges of implementing data mesh on Azure data lake? Does it have any key advantages to other architectures such as hub and spoke? How is implementation to be started?

Answer 1

Hello Anshal,

Greetings! Welcome to Microsoft Q&A Platform.

1.Data mesh is an architectural pattern for implementing enterprise data platforms in large and complex organizations. Data mesh helps scale analytics adoption beyond a single platform and a single implementation team. Hence, it's not required to create separate data lake for each department and data mesh doesn’t mandate separate data lakes for each department. Instead, it encourages domain teams to own and manage their data within a shared data lake or platform.

refer - https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/architectures/what-is-data-mesh for detailed guidance.

2.Data consolidation happens through domain-specific data products. These products are created by domain teams and can be shared across other domains. In a data mesh, integration happens through well-defined APIs (data products) created by domain teams. These APIs allow cross-domain access to data.

3.Each domain team has its own security and access requirements, managing fine-grained access control across domains can be complex and hence leverage Azure Data Lake’s access control features, such as ACLs (Access Control Lists) and RBAC (Role-Based Access Control). Define roles and permissions based on domain needs.

4.When using data mesh, take special care when implementing your governance so you don't create silos. Always keep product thinking for data at the core of your implementation to ensure success. Data mesh distributes ownership and responsibility to domain teams. Each domain team manages its data products, and it scales horizontally as more domain teams contribute data products. Teams can access and analyze their data independently.

refer - https://techcommunity.microsoft.com/t5/analytics-on-azure-blog/establishing-data-mesh-architectural-pattern-with-domains-and/ba-p/3924745 for more details.

Hope this answer helps! Please let us know if you have any further queries. I’m happy to assist you further.

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