Data Architecture & Strategy
91 posts filed under Data Architecture & Strategy.
Stack Tool Confusion Signs
Nobody wants to be the one who questions the tool the last person bought before they left.
Read →Databases Are Being Redesigned for AI Workloads
Postgres handled it fine. Until the agent started issuing thousands of embedding lookups a second.
Read →Real-Time Failure Modes
Duplicate invoices came from the recovery, not the outage. The retry replayed 40 minutes into a double-counting sink.
Read →Observability Blast Radius
A failure that cost one dashboard last year now takes out 40 downstream jobs. The platform grew. The alerts didn't.
Read →Data Mesh Readiness For 50+
A 60-person scaleup asked me to design their data mesh. After the readiness check, we kept the central team.
Read →BigQuery Vs Snowflake For Ad-Hoc
BigQuery vs Snowflake for ad-hoc work comes down to one choice: pay per scan or pay per minute.
Read →Iceberg Is Open. Your Security Model Isn't
An auditor asked who could read the customer table. With three engines on one Iceberg catalog, nobody could answer.
Read →AI Modeling Crisis Patterns
Every failed RAG project I've reviewed had the same upstream issue: nobody modeled the data underneath it.
Read →Data Product Canvas Update For AI Consumers
Your newest data consumers don't file tickets. They're AI agents, and they break differently.
Read →Too Deep Into Snowflake" Is an Architecture Smell
You can measure architecture health by the price of an exit. For one stack I reviewed, it was 18 months.
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