Power Query is your secret weapon for rapid prototyping—and now it can become the bridge between analytics and engineering teams. Leverage the business logic you've already perfected in Power Query as a shared design language, then seamlessly convert proven prototypes into production-grade Fabric pipelines that scale to enterprise data volumes.

What you'll master:
- Apply Power Query as a rapid prototyping tool that validates transformation logic and communicates requirements to data engineering teams in a language both sides understand
- Implement Medallion Architecture (Bronze, Silver, Gold) to structure scalable, maintainable data pipelines that serve both BI and engineering needs
- Convert Power Query prototypes to Fabric Notebooks preserving business logic while gaining enterprise performance and orchestration
- Design effective handoff documentation** that translates Power Query transformation steps into clear data engineering requirements with testable acceptance criteria
- Leverage AI coding agents and skills to auto-generate Fabric Notebooks from Power Query prototypes, validate transformations, and accelerate the transition from prototype to production code
- Build end-to-end Fabric Data Pipelines with orchestration, error handling, and incremental refresh patterns—using AI-assisted development techniques throughout

Prototype fast in Power Query, align your teams around a shared specification, and deploy production pipelines that scale to billions of rows—turning your existing BI expertise into a data engineering superpower.

- Target Audience: Power BI developers expanding into data engineering, analytics engineers, data engineers collaborating with BI teams, team leads managing analytics-to-engineering handoffs
- Format: 45-minute talk or full-day hands-on workshop
- Takeaways: Medallion Architecture templates, Power Query to Notebook conversion guide, requirements handoff template for analytics-to-engineering collaboration, pipeline patterns
- Prerequisites: Intermediate Power Query experience, basic understanding of data pipeline concepts
- Level: Intermediate to advanced
- Topics Covered: Power Query, Microsoft Fabric, Fabric Notebooks, Medallion Architecture, Data Pipelines, Requirements Communication