Data Architecture · Quantitative Systems · Analytics
Building systems that turn data into decisions
Long-form essays on the architecture decisions that age well, paired with the production systems that test them. Written and operated by an independent senior practitioner.
Leaving the cloud is neither a rejection of managed infrastructure nor a universal cost-savings strategy. The useful question is where each workload belongs after its demand, data gravity, coupling, regulation, and operating capacity are visible.
The compact working version of the exit-cost article: a one-page review frame for vendor selection, renewal, and architecture risk discussions.
Vendor selection usually prices adoption, not departure. The architectural question is what it would cost to leave when the business, license, price, or operating model changes.
Every proprietary dependency is a future rewrite. Why open source first is an infrastructure decision, not an ideology — and why exit cost is the system property nobody designs but everyone eventually pays for.
Cloud platform commitment is the largest architectural decision most teams make, and the one most often made invisibly. Why "best service for the job" produces a system whose exit cost the vendor sets.
PCA is a linear algebra operation, not a magic wand. It finds directions of maximum variance — but variance isn't signal. When financial data violates every assumption PCA makes, "90% explained variance" might mean you've captured 90% of the noise.
AI makes custom tooling accessible to anyone who understands the underlying systems. The value of knowing how things work keeps going up, not down.
A short review frame for pricing departure before a vendor decision hardens into architecture. Built for architecture reviews, renewals, and vendor-selection work.