Part I
The infrastructure layer that makes ML possible. Warehouses, lakehouses, pipelines, streaming, orchestration, and the data quality practices that separate production systems from prototypes.
From raw business events to analytical systems: warehouses, lakehouses, pipelines, streaming, orchestration, quality, and governance.
Feature stores, training data at scale, dataset versioning, LLM data pipelines, vector databases, and production feedback loops.