Armchair Architects: Data Mesh Architecture

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? learn.microsoft.com/en-us/azu...
• Manage master data in data mesh learn.microsoft.com/en-us/azu...
• A financial institution scenario for data mesh learn.microsoft.com/en-us/azu...
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 paying attention to in the world of data meshes?
To watch more episodes in the Armchair Architects series, check out this playlist! aka.ms/armchairarchitects
To watch more episodes in the Well-Architected series, check out our playlist! aka.ms/azenable/yt/wa-playlist