Microsoft Fabric – Clear mental model and end-to-end architecture

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#82 opened on Feb 9, 2026 1 comment 1 reaction 0 assignees View on GitHub

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Assessment

Difficulty: 4/5
Estimated time: 3-5 days
Newbie friendliness: 35/100

Issue type: Documentation
Clarity: Mostly clear
Activity status: Stale
Domain: cloud, documentation

Research direction

Start with the Microsoft Fabric overview documentation, Microsoft Learn’s “What is Microsoft Fabric?”, and the Fabric architecture and OneLake documentation. Produce a cohesive explanation of how OneLake, Lakehouse, Warehouse, Data Engineering, Data Factory, Data Science, Real-Time Analytics, and Power BI fit together, including typical data flows and conceptual differences from Azure Synapse, Data Factory, and ADLS.

Written by the indexing model from the issue text.

Description

Note request

What concept do you need more clarity on?

I’m looking for a clear, practical explanation of Microsoft Fabric’s overall architecture and mental model.
Specifically, how the core components (OneLake, Lakehouse, Warehouse, Data Engineering, Data Factory, Data Science, Real-Time Analytics, Power BI) fit together, when to use each, and how data typically flows across them in real-world scenarios.

The goal is to understand Fabric not as separate tools, but as one integrated platform, including how it differs conceptually from traditional Azure Synapse + Data Factory + ADLS setups.

Any reference explaining that concept

Microsoft Fabric overview documentation

Microsoft Learn: “What is Microsoft Fabric?”

Fabric architecture and OneLake documentation

Community blogs comparing Fabric vs Synapse

Official Fabric announcements and Ignite sessions

(References explain parts well, but a single, cohesive mental model is missing.)

Have you checked the list of issues to see if there is a similar suggestion?

Yes, I have checked

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Forks: 31
Avg merge: 4d 13h
Merged PRs (30d): 1

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