How to design reliable data pipelines : four architectural layers, failure handling patterns, and the composable pipeline approach.
How to think like a data engineer : principles over tools, the Five Questions Framework, systems thinking, and designing for failure first.
Seven common data modeling mistakes and how to avoid them : from naming conventions to governance integration.
A deep dive into Data Vault modeling : Hubs, Links, and Satellites explained with examples, and how to present Data Vault output for analytics consumption.
