Implementing Data Lakes and Lakehouses in Fabric

Modern organizations need scalable, unified data platforms to turn raw data into actionable insights without complex, siloed infrastructure. Fabric offers a revolutionary, unified analytics platform that simplifies data lakehouse implementation. This comprehensive text-based course guides you through the process of setting up, structuring, and managing a modern lakehouse architecture. In this course, you will transition from understanding basic cloud storage to designing robust data pipelines. Through clear, written explanations and practical code snippets, you will master the principles of modern data engineering and learn how to maintain high-performance data environments. What you'll learn: - Understand the core concepts of data lakes, lakehouses, and the unified Fabric ecosystem. - Configure workspaces and lakehouse environments to store structured and unstructured data. - Apply the medallion architecture (Bronze, Silver, and Gold layers) to organize and refine data. - Write PySpark and SQL queries inside notebooks to clean and transform raw datasets. - Implement Delta Lake tables to ensure ACID compliance and optimal query performance. - Connect your lakehouse to reporting tools using Direct Lake mode for efficient data access. This course begins with essential terminology, architectural foundations, and basic configurations before moving into practical data ingestion and transformation techniques. You will progress through structured, text-guided exercises designed to simulate real-world data engineering scenarios. This course is designed for beginner data analysts, aspiring data engineers, and database administrators looking to modernize their data stack. No prior experience with Fabric is required. Start reading today to build and manage your first modern data lakehouse.