Why data quality is a pipeline problem, not a dashboard problem : six dimensions of quality, validation strategies, and monitoring patterns.
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.
