Notes on dataarchitecture.
Short essays on architecture, cost, hiring and AI: one cartoon, one idea, most days of the week. No tutorials, no listicles.
Fitness Functions: Testing Your Architecture Like Code
You test your code. You test your data. But who tests your architecture? Here's how fitness functions change that.
Read →The 306K Per Million Lines: What Technical Debt Actually Costs
Nobody budgets for technical debt. But it budgets itself - in slow changes, frequent bugs, and engineers who quit.
Read →The Hybrid Governance Rollout: From Bottleneck to Balance in 12 Weeks
Every governance rebuild I've seen starts the same way: a team that over-corrected once, then over-corrected the other way, and is now tired …
Read →Status Quo Is Never Free: Why Your 'Do Nothing' Option Has the Biggest Hidden Price
"Do nothing" is never free. One client's "zero cost" status quo was burning 200K a year in workarounds nobody tracked.
Read →CAP Per Workload: Why One Consistency Model Doesn't Fit Your Whole Platform
Treating finance and customer analytics like the same workload is how you end up with a platform that serves neither well.
Read →The Rise of Data SRE: Reliability Engineering for Data Platforms
Your data pipelines run in production. But nobody treats them like production systems. That's about to change.
Read →Observability Turned Our Senior Engineers Back Into Builders
Six months ago our senior engineers were firefighters. Now they're builders again. The change wasn't a reorg. It was observability.
Read →The Data Maturity Assessment You Can Do in 30 Minutes
Most maturity assessments take six weeks and a consulting firm. This one takes 30 minutes and a whiteboard.
Read →The Data Quality Crisis: 67% of Executives Don't Trust Their Analytics
Executives stopped using the dashboards. They didn't trust the data. Here's how we rebuilt trust in 10 weeks.
Read →Wardley Mapping Your Data Stack (Build, Buy, or Outsource?)
Your custom Airflow setup is not a competitive advantage. Your customer analytics model might be.
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.