Config-Driven Data Engineering in Microsoft Fabric

Many Fabric implementations start with a handful of PySpark notebooks and quickly face the same challenge: how to manage, reuse, and orchestrate them at scale. Without structure, integrations become fragile, inconsistent, and difficult to promote across environments. This session explores a practical architecture that turns ad-hoc notebooks into reusable, auditable, and production-ready assets.

We’ll walk through the principles behind configuration-based orchestration, modular notebook patterns, and dynamic pipeline generation within Fabric. Learn how declarative metadata can drive transformations, handle slowly changing dimensions, manage schema evolution, and enable environment layering for dev/test/prod deployments while still aligning with Fabric’s native Pipelines, Lakehouses, and Delta format.

The session demonstrates how these principles translate into cleaner operations: faster onboarding for new datasets, simpler maintenance, and transparent governance. By standardizing how notebooks interpret configuration, teams can deliver new integrations in days instead of weeks while preserving full auditability and control.

Attendees will leave with actionable patterns they can apply immediately to modernize their own Fabric environments and establish the foundation for a scalable, metadata-driven integration framework.

AI in Microsoft Fabric: A Guided Tour of Features and Use Cases

Microsoft Fabric is evolving into a powerful platform for unified data and AI workflows. In this session, we’ll explore the AI features woven into the Fabric experience from CoPilot and Data Agents (formerly AI Skills) to built-in AI functions that enhance how you interact with and analyze your data. This technical overview will introduce each capability, explain its use case, and demonstrate how you can get started. Whether you're a developer, analyst, or architect, you'll walk away with a solid understanding of how Microsoft Fabric empowers AI-driven experiences.

Presented: M365 Community Days - Saint Louis 2025

Applying Medallion Architecture in Microsoft Fabric: Principles, Patterns, and Pitfalls

Medallion architecture provides a proven framework for structuring modern data lakes—but applying it effectively in Microsoft Fabric requires a pragmatic understanding of both the platform and the business context. This session explores how the medallion model translates into Fabric's components, from Lakehouses to Pipelines to Power BI. Learn practical design patterns, common implementation challenges, and real-world lessons from the field to help you build a scalable, governed, and insight-ready data platform.

Presented: SQL Saturday St. Louis 2025

Modern CI/CD Approaches for Microsoft Fabric

Applying CI/CD in Microsoft Fabric is less about chasing a single “perfect” pattern and more about adopting a maturity path that matches your team’s reality. Fabric offers native building blocks (Git integration and deployment pipelines), but real-world DataOps outcomes require decisions about workspace tiering, branching discipline, release packaging, and environment-aware configuration.

We’ll walk through practical deployment approaches ranging from Fabric deployment pipelines to code-driven automation using GitHub Actions or Azure DevOps, and where supporting tooling like VS Code, the Fabric CLI, and Terraform can help round out a more complete DataOps operating model. Along the way, we’ll address the real-world friction points that commonly slow teams down in Fabric, including how to keep development continuously releasable, how to manage data readiness across environments when data itself isn’t versioned in Git, and how to handle cross-environment reference drift when asset identifiers change between workspaces.

The session includes live demos that walk through representative end-to-end workflows, from making a change in a feature branch to promoting a tested release through environment tiers using both Fabric-native and code-driven approaches. You’ll leave with a practical decision framework for choosing the right CI/CD pattern for your team’s current maturity, plus a concrete branching and environment strategy you can adapt immediately to reduce deployment risk and improve team velocity.

Who should attend: data engineers and technical leads who need to collaborate safely, isolate development from production, and evolve Fabric DataOps without turning it into an all-or-nothing transformation.

What you’ll take back: a clear maturity roadmap, a defensible branching and workspace strategy, and proven patterns for moving from “we deploy changes” to “we can release confidently.”