Notes on dataarchitecture.

Short essays on architecture, cost, hiring and AI: one cartoon, one idea, most days of the week. No tutorials, no listicles.

Five times the data. Same number of people. No new hires. The only way through? Rethink the architecture.

Data observability sounds expensive and complex. Here's how to start in one afternoon.

A data architecture review uncovers hidden risks before they become expensive problems. Here's what mine covers and why most teams need one …

Your nightly job reprocesses 10TB. Only 50GB changed. You're burning money and adding risk.

You don't always need a data architect consultant. Here's how to know if you do, what to expect, and how to avoid hiring the wrong person.

We spent a decade optimizing compilation times. Now we're staring at an LLM spinner doing the exact same thing.

Nobody sets out to hoard knowledge.

You wouldn't ship a software product without an owner, a roadmap, or a release process. Why do you treat your data differently?

Slow pipelines are a symptom. The disease is poor architectural decisions nobody revisited.

Your second data platform will be overengineered. Fred Brooks predicted this in 1975.

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.