Lakehouse Patterns for Unifying Analytics and ML Datasets
When you’re building modern data platforms, one of the most persistent challenges is the artificial divide between analytics and machine learning workflows. Data teams maintain separate pipelines—one feeding data warehouses for BI dashboards and SQL analytics, another feeding data lakes or feature stores for ML training and inference. This duplication wastes resources, creates consistency problems, … Read more