In the age of cloud analytics, today’s best practice is tomorrow’s legacy. Microsoft Fabric aims to be the one platform that rules them all, bringing together data engineering, warehousing, and visualization in a single Software-as-a-Service (SaaS) package. At the heart of this platform, Fabric Data Warehouse delivers a familiar yet modern T-SQL–based experience that is scalable, cloud-native, and tightly integrated with the broader Fabric ecosystem. It supports multiple ingestion and transformation paths. It provides practitioners flexibility with how data is landed and shaped whether streaming, batch, or metadata-driven. Just as importantly, Fabric data warehouse is designed to serve not just as a single central repository, but as a collection of purpose-built warehouses that can coexist and scale within an environment, aligning with both technical best practices and business needs. With its seamless integration to Power BI, Fabric empowers data professionals to shorten the path from raw data to actionable insights, while providing the governance and lifecycle tools needed to manage growth and change over time.

The landscape of data roles and technologies is rapidly shifting. Many professionals find themselves as “accidental” data warehouse practitioners that are tasked with designing and implementing warehouses without formal training, simply because the responsibility landed on their desk. At the same time, long-standing on-premises data warehouses are being retired in favor of cloud-native platforms, and Power BI datamarts are being phased out with Fabric Data Warehouse emerging as the recommended successor. Together, these changes are reshaping how organizations think about their data architecture and how individuals must adapt their skills to thrive in a modern analytics environment.

The presenters are experienced data warehousing practitioners who will guide attendees through the patterns, practices, and pitfalls of Microsoft’s modern approach to data warehousing in Fabric. Drawing on real-world expertise, they will highlight both the opportunities and the challenges of adopting Fabric DW, from modeling fundamentals to ingestion strategies and lifecycle management. Attendees will leave the session with a clear understanding of how to design and manage effective warehouses in Fabric, avoid common mistakes, and apply proven techniques that accelerate success in their own environments.

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.