22-25 April 2026 
Small Team, Medium Data: A Fabric Implementation Journey
Proposed session for SQLBits 2026TL; DR
A candid, step-by-step story of taking Microsoft Fabric from demos to production as a small team in a big org: architecture, governance, capacity, CI/CD, monitoring, and the wrong turns that taught us what works.
Session Details
We've seen the Fabric demos. The hard part is making it something your business will rely on.
In this grounded-in-reality session, I’ll walk through how our small analytics team at a Tier 1 automotive manufacturer took Fabric from first concepts to a production data platform in two years: what worked, what didn’t, and the trade-offs behind our decisions.
We’ll cover the architecture we landed on (and why), how we structured workspaces and data products, and the practices that turned Fabric into something we could support: capacity planning and monitoring, metadata-driven pipelines, adoption and governance, CI/CD and deployment patterns, and how we try to realize the promised land of managed self-service BI.
Expect specific patterns, wrong turns, and pragmatic lessons to shorten your own path to “Fabric, in production.”
In this grounded-in-reality session, I’ll walk through how our small analytics team at a Tier 1 automotive manufacturer took Fabric from first concepts to a production data platform in two years: what worked, what didn’t, and the trade-offs behind our decisions.
We’ll cover the architecture we landed on (and why), how we structured workspaces and data products, and the practices that turned Fabric into something we could support: capacity planning and monitoring, metadata-driven pipelines, adoption and governance, CI/CD and deployment patterns, and how we try to realize the promised land of managed self-service BI.
Expect specific patterns, wrong turns, and pragmatic lessons to shorten your own path to “Fabric, in production.”
3 things you'll get out of this session
- Identify the capabilities you need before your org can call Fabric “in production.”
- Evaluate real architecture and governance trade-offs using a real implementation.
- Learn from our mistakes to avoid common dead ends.