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

Data Warehouse vs Data Lakehouse vs Data Lake

In today’s data-driven world, organizations face an overwhelming challenge: how to store, manage, and analyze massive volumes of data efficiently. The evolution of data storage architectures has given us three primary approaches—data warehouses, data lakes, and the newer data lakehouse. Each serves different purposes and offers unique advantages, making the choice between them crucial for … Read more