Notes on dataarchitecture.
Short essays on architecture, cost, hiring and AI: one cartoon, one idea, most days of the week. No tutorials, no listicles.
What Is a Data Architect?
Data engineers solve problems. Data architects help decide which problems are worth solving.
Read →Architecture Advisory: The 3 Questions I Ask First
In week one of any architecture review, I ask the same 3 questions.
Read →Why Your AI Project Failed at the Data Layer
Rule of thumb: AI success is 20% model and 80% data infrastructure.
Read →Legacy Modernization: Break or Transform
Some legacy systems should be replaced. Most should just be wrapped.
Read →Hero Dependency: Why Your Best Work Makes You Replaceable
The best proof of your value is a team that doesn't need you anymore.
Read →Shadow Data Costs Your Team 8-9 Hours/Week
Your team can lose 8-9 hours/week to shadow data. And they actually don't call it that.
Read →GenAI Risks: The Billion-Euro Wake-Up Call
GenAI failures are poised to cost enterprises billions in wasted budget. Many won't be tech failures.
Read →Team Alignment Sprint: 3 Outputs Teams Actually Use
A 4-week sprint. 3 outputs. Zero slide decks nobody reads.
Read →You're Hiring Data Engineers Wrong
You're hiring data engineers wrong. And your best candidates know it.
Read →FinOps Reality Check: 60% Wasted Spend
Up to 60% of your cloud spend can go to waste. And nobody owns the problem.
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.