Armchair Architects: Data Mesh Architecture

From the creator

Data meshes are an architectural pattern for implementing enterprise data platforms in large, complex organizations. Data meshes help scale analytics adoption beyond a single platform and a single implementation team. In this episode of the #AzureEnablementShow, David, Uli, and Eric (@mougue) discuss what makes up a data mesh, what data meshes do (and don’t do), when they are appropriate, and what architects should be paying attention to going forward. Resources • What is a data mesh? https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/architectures/what-is-data-mesh • Manage master data in data mesh https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/architectures/data-mesh-master-data-management • A financial institution scenario for data mesh https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/architectures/data-mesh-scenario Chapters 0:00 Introduction 1:00 Data Mesh Architecture has two main components: data silos and implementation 2:57 Data meshes should contain a very strong governance model 6:20 Why is the Governance Model not a Discovery Model? 7:10 Data is usually passive and requires a query or some other action to be discoverable 8:07 Data meshes help determine what data you have and who has access to it 10:30 Data meshes aren’t appropriate for all use cases 12:46 Are data meshes aspirational? 14:20 What should people be payin

Published 2023-03-14 · Watch on YouTube ↗
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