Resources
How we build data platforms, written down: deep-dive case studies, practical guides, and templates you can copy into your own repo.
How a config-driven pipeline moves every source through Bronze, Silver and Gold, hashes PII on the way, and hands dbt one model per Airflow task.
Auto Loader, rescued columns and drift alerts, so a new field upstream never breaks a dashboard downstream.
A marketing mart on Redshift and dbt that feeds both models, and how the budget team uses the results.
fct_touchpoints, dim_campaigns and friends, with keys, tests and docs already wired up.
One identity across email, phone and address pools, without storing raw personal data in your marts.
Why we split dbt runs per model, and what it does to retries, lineage and on-call sleep.
Grounding Genie and Claude in tested dbt models and metric definitions so answers match the dashboard.
Nothing here yet. This pond is still filling up.
Downloads
32 questions to answer before you pick a warehouse, from source inventory to who owns each metric.
Get the checklistName, grain, formula, owner and source model for every KPI, so finance and marketing stop arguing.
Get the templateStaging, intermediate and marts folders with naming rules, tests and CI checks you can run on day one.
Get the skeleton