Part 3: Solving Real-World Problems with Transformational Modeling

This part focuses on advanced transformational modeling techniques and covers the theory and practice of putting them into action in Snowflake. First, we explore slowly changing dimensions—critical for maintaining historical data accuracy and ensuring consistency across different versions of data. Then, we learn how to model facts for rapid analysis, including best practices for optimizing query performance. We then explore semi-structured data formats and hierarchies, which are becoming increasingly prevalent and which Snowflake is so adept at handling. This part also covers the basics of Data Vault methodology for building agile, scalable, and auditable architectures, as well as Data Mesh, which is becoming an increasingly popular approach to managing data domains at scale across large organizations. Finally, you will experiment hands-on with fun and effective SQL recipes that couldn’t be included...