Practical Kimball Data Patterns for Machine Learning Data Warehousing

Learn how to effectively implement Kimball data patterns for machine learning in this 31-minute conference talk from DSC ADRIA 2023. Explore why 85% of Machine Learning projects fail and how proper data warehousing can address the challenge of data scientists spending 80% of their time on data preparation. Follow along as Antoni Ivanov demonstrates the creation of a Data Warehouse, implements a star schema using Kimball methodology, and applies it to a simple ML model. Gain insights into the advantages and limitations of using Warehousing design patterns in machine learning projects, with a focus on achieving clean, well-structured datasets that follow the one observation per row and one variable per column principle.