What you'll learn

Modern data lakes often suffer from inconsistent table access, schema drift, and challenges in running queries across multiple compute engines. In this course, Open Table Format Architecture and Metadata Models, you’ll gain the ability to design, manage, and optimize open table formats and catalogues for reliable, scalable, and engine-agnostic analytics. First, you’ll explore how open table formats organize data files, metadata layers, and snapshots to ensure consistency and scalability. Next, you’ll discover snapshot isolation, partitioning strategies, and schema evolution mechanisms that enable safe concurrent reads and writes. Finally, you’ll learn how catalogs, interoperability standards, and multi-engine best practices empower consistent table discovery, governance, and cross-engine query execution. When you’re finished with this course, you’ll have the skills and knowledge of open table formats and metadata models needed to implement robust, scalable, and engine-neutral data pipelines, ensuring consistent analytics and future-proof data lake architectures.