Notes on dataarchitecture.
Short essays on architecture, cost, hiring and AI: one cartoon, one idea, most days of the week. No tutorials, no listicles.
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 →When You Actually Need a Modern Data Stack
Your spreadsheet chaos isn't a sign you need Snowflake. It's a sign you need clarity on what you're trying to measure.
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.