Fabric BI Architecture: Patterns, Workspaces, and Trade-offs

"How should we structure our Fabric workspaces?" It's one of the first questions I get in any engagement, and my answer is always: it depends. I've seen teams pick patterns that look clean on a diagram but fight against them for months. The challenge isn't finding an architecture — it's choosing one that actually fits your situation.

In this session, I'll walk through common BI architecture patterns and how they translate into Fabric workspaces. We'll look at what works, what gets complicated, and where decisions made early can cause friction later, especially when deployment pipelines only support one workspace at a time.

We'll cover:

- Common patterns: separating data engineering and analytics environments, layered architectures, locking down elements with private links
- How workspace structure supports (or fights against) your architecture
- Access control, identities, and who can see what
- Deployment and lifecycle: what changes when you have multiple workspaces
- The trade-offs behind each approach and how to choose

You'll leave with reference architecture diagrams you can adapt, and a clearer sense of how to match your architecture to your organisation's needs. Whether you're designing from scratch or rethinking an existing setup, this session will help you make decisions with your eyes open.

- Common patterns: separating data engineering and analytics environments, layered architectures, locking down elements with private links - How workspace structure supports (or fights against) your architecture - Access control, identities, and who can see what - Deployment and lifecycle: what changes when you have multiple workspaces - The trade-offs behind each approach and how to choose