Seattle, WA

Design a Well-Architected Fabric Solution: A Medallion First Approach

Tuesday 9:00 AM - 5:00 PM · Room 344

Design a Well-Architected Fabric Solution: A Medallion First Approach

Reid Havens

Reid Havens

Founder | BI Evangelist - Havens Consulting

Steve Campbell

Steve Campbell

Co-Founder @ Analytic Endeavors, MVP

Transform your data solutions with a streamlined Medallion Architecture using Microsoft Fabric. This session is tailored for professionals familiar with Power BI and basic dataflows, providing a step-by-step guide to implementing Bronze, Silver, and Gold layers for a scalable and maintainable pipeline. Learn how to evolve an unstructured dataflow and semantic model into a comprehensive architecture. Familiarity with Python or SQL is a bonus but not required.

Modules: • Overview of Medallion Architecture: Gain a clear understanding of Warehouses and Lakehouses, their role within Microsoft Fabric, and how they enable Medallion Architecture. • Understanding OneLake: Dive into OneLake and explore its foundational storage structure, including Delta tables and Parquet. Understand key features like columnar storage, Delta optimizations, and performance enhancements through simple, no-code explanations. • Feature Showdown: Compare and contrast key tools in Microsoft Fabric, such as SQL vs. Spark, Notebooks vs. Dataflows vs. Pipelines, and Warehouses vs. Lakehouses, to determine the best fit for your scenarios. • Well-Designed Architecture & Best Practices: Learn about GIT integration, monitoring techniques, and actionable best practices for designing scalable and maintainable data architectures.

Labs: • Build a Lakehouse and create a Medallion Architecture pipeline. • Extract raw data using Pipelines (Bronze). • Clean and transform data with Spark Notebooks (Silver). • Add business logic with T-SQL (Gold). • Create orchestration and monitor pipelines for optimal performance. • Bonus Lab: Create and manage a semantic model and integrate it with GIT for version control.

 

X Close

Keep Up to Date on
DATACON