Data Lakehouse Fundamentals: Build and Analyze Modern Architectures

Traditional data architectures often force you to choose between the structure of a data warehouse and the raw storage power of a data lake. The modern data lakehouse architecture solves this by merging both approaches into a single, high-performance system. In this text-based course, you will transition from understanding basic storage concepts to confidently designing and querying a modern data lakehouse. You will learn how to maintain data quality, enforce schemas, and prepare your data for real-time analytics and AI workloads. What you'll learn: - Understand the core principles and architectural layers of a modern data lakehouse - Implement open table formats like Delta Lake to enable ACID transactions on raw storage - Query and analyze structured and semi-structured data using SQL and modern analytical engines - Apply schema enforcement and evolution strategies to maintain high data quality - Configure data governance, access controls, and cataloging for secure collaboration - Prepare your lakehouse architecture to support downstream machine learning and business intelligence This course begins with essential terminology, comparing traditional databases, lakes, and warehouses before moving into practical table formats, storage optimization, and analytical querying techniques. Designed for aspiring data engineers, analysts, and database administrators new to lakehouse concepts, this course requires no prior data engineering experience. Start reading today to master the next generation of data storage and analytics.