Notes on dataarchitecture.
Short essays on architecture, cost, hiring and AI: one cartoon, one idea, most days of the week. No tutorials, no listicles.
Metadata Management ROI
Engineers losing 10-20% of their time to repetitive questions. Most teams don't even measure it.
Read →Data Quality Testing Layers
Testing data quality after transformation is like tasting the dish after it's plated. Too late.
Read →Technical Debt Productivity Loss
Every data engineer on your team loses 2 days per week to technical debt. That's time they can't spend building.
Read →The €250K Migration That Didn't Need to Happen
The €250K migration wasn't a technology project. It was an expensive way to avoid hard conversations.
Read →Building data platforms for technology instead of teams
The data platform nobody asked for is the data platform nobody uses.
Read →Event-driven architecture coordination tradeoffs
You adopted EDA to reduce dependencies. You just traded runtime coupling for design-time coupling.
Read →Data Architecture vs Data Engineering: What's the Difference?
Architects design the blueprint. Engineers build the system. Hire the wrong one first and you'll hire both twice.
Read →mise en place for data teams
Skip your prep and service falls apart. Every chef knows this. Most data teams learn it the hard way.
Read →The Alignment Tax: What Misalignment Costs Per Sprint
Your team's velocity isn't slow because they're bad. It's slow because they're building the wrong thing right.
Read →The AI Readiness Checklist Nobody Uses
Every company has an AI roadmap. Almost none have passed their own readiness checklist.
Read →Want expert eyes on your data architecture?
No pitch. An honest conversation about whether I can help, and what shape it would take if I can.