Apache Iceberg enhances machine learning workflows by addressing reproducibility issues through time travel, schema evolution, and ACID transactions, enabling reliable data management in data lakes. The article highlights how Iceberg's features can significantly improve query performance, reduce debugging time, and facilitate the addition of new features without disrupting existing pipelines. These capabilities help data engineers manage data drift and maintain consistent model performance in production.