Data Architecture & Strategy
102 posts filed under Data Architecture & Strategy.
Postgres Or A Real Warehouse First
Postgres can probably carry your analytics longer than you think.
Read →The Stack You Actually Need At 15 Engineers
At 15 engineers, a data stack with twelve tools is mostly twelve invoices and one tired person.
Read →Coalesce Context As Infra
Treat your metric definitions like a Terraform file, or keep the agent away from them.
Read →Semantic For Unstructured First
Most AI data problems I see start in a column called payload, long before any embedding.
Read →Orchestration Consolidation Matrix
Count the places a job can be scheduled in your data stack. Include the cron on that one VM.
Read →dbt Coalesce Metadata Shift
The description fields in your dbt project used to be read by nobody. Now an agent reads them.
Read →Governance Before AI Act Fines
The provenance record behind an AI feature fits in a YAML file next to the pipeline code.
Read →Rust Is Quietly Becoming the Language of Data Infra
The fastest tools in your data stack are written in a language nobody on your team writes.
Read →Pipeline Novelty Implementation
Novel data projects tend to die between the team that built the prototype and the team stuck running it.
Read →Ownership Before Governance
A 20-page data governance policy with no named owners is a document nobody can enforce.
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