Notes on dataarchitecture.
Short essays on architecture, cost, hiring and AI: one cartoon, one idea, most days of the week. No tutorials, no listicles.
The 6 Dimensions of Data Quality
Data quality has 6 dimensions. Most teams only measure 2. Here's what you're missing.
Read →The Three Ways Applied to Data Pipelines
Your data team ships pipelines fast. That's the First Way. They're ignoring the other two.
Read →Platform Scaling Without Hiring
Five times the data. Same number of people. No new hires. The only way through? Rethink the architecture.
Read →Data Observability Practical Start
Data observability sounds expensive and complex. Here's how to start in one afternoon.
Read →Data Architecture Review - What's Actually Involved
A data architecture review uncovers hidden risks before they become expensive problems. Here's what mine covers and why most teams need one …
Read →Incremental Processing Pattern
Your nightly job reprocesses 10TB. Only 50GB changed. You're burning money and adding risk.
Read →Why Companies Hire a Data Architect Consultant (And When You Shouldn't)
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.
Read →Waiting for LLMs vs Waiting for Compilation
We spent a decade optimizing compilation times. Now we're staring at an LLM spinner doing the exact same thing.
Read →Cost of Tribal Knowledge
Nobody sets out to hoard knowledge.
Read →Data Product Operating Model
You wouldn't ship a software product without an owner, a roadmap, or a release process. Why do you treat your data differently?
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.