In the age of cloud analytics, today’s best practice is tomorrow’s legacy. Microsoft Fabric positions itself as the rebel alliance to this chaos, a single platform uniting data engineering, warehousing, and visualization in one SaaS package. Within this universe, the Fabric Data Warehouse awakens as a powerful yet approachable force: a T-SQL–based engine that works seamlessly with multiple ingestion and transformation patterns, from batch loads to streaming flows. But unlike the Death Star, this isn’t about building one massive monolith. The true power lies in creating multiple purpose-built warehouses that coexist, scale, and adapt to your business needs. With native integration to Power BI, Fabric makes it easier for practitioners to bring order to their data galaxy, while avoiding the dark side of accidental complexity.

The data galaxy is in flux, and with it, the roles of those who navigate it. Many have become “accidental” data warehouse practitioners through volunteering (or perhaps being voluntold) to build warehouses without the benefit of a proper training academy. Meanwhile, the old on-prem strongholds are fading into legend as organizations make the jump to cloud hyperspace. Even Power BI datamarts, once a trusty starfighter for quick solutions, are being decommissioned, with Fabric Data Warehouse now the recommended vessel for the battles ahead. For data professionals, this isn’t just a shift in tooling. It’s a new chapter in the saga, where adapting to change determines whether you stay a padawan or become a true Fabric master.

The presenters are seasoned data warehouse Jedi, ready to share the patterns, practices, and pitfalls of Microsoft’s modern approach to data warehousing in Fabric. Through demos and stories from the trenches, they’ll illuminate both the light side (what works well) and the dark side (what to avoid) of Fabric DW, covering everything from modeling to ingestion to lifecycle management. Attendees will leave the session equipped with their own lightsaber of knowledge, prepared to build, monitor, and scale Fabric warehouses without falling victim to the traps of accidental complexity.

Contents:
• Part 1 - Patterns: Dimensional data modeling
• Part 2 - Patterns: Data Warehousing fundamentals
• Part 3 - Patterns: Ingestion and medallion architecture
• Part 4 - Practices: Change detection
• Part 5 - Practices: Data warehouse life cycle and CI/CD
• Part 6 - Practices: Monitoring and administration
• Part 7 - Practices: Migrations
• Part 8 - Pitfalls: Tips and tricks on how to avoid them

Intended Audience:
• "Accidental" data warehousing professionals, or those looking for a refresher on the theory and techniques of data warehousing in Fabric.
• Folks needing to migrate from an on-premises data warehouse or from Power BI datamarts to Fabric.
• The focus is on data warehouse development and data engineering. The content may be less applicable for those whose primary role is report building and/or data analysis.
• The content is aimed at the doers, not the delegators.