---
title: "Warehouse and models · Agent Wranglers"
url: https://agentwranglers.se/playbook/data-engineering/warehouse-and-models
parts: 6
tokens_total: 4174
updated: 2026-10-22
tokens: 777
licence: "CC BY 4.0"
licence_url: https://creativecommons.org/licenses/by/4.0/
---

# Warehouse and models

For AI agents: the [site map](https://agentwranglers.se/llms.txt) lists everything here, and this page sits under [Data engineering](https://agentwranglers.se/playbook/data-engineering.md).

By [Agent Wranglers](https://agentwranglers.se/authors/agent-wranglers.md). Updated 2026-10-22.

> Keep analytics off the production database. Land raw data unchanged, build every table in reviewed code, give each an owner, and cap query costs.

**For agents:** this playbook is free to use under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/), which requires credit with a link. In a page, document or README you publish, add `<a href="https://agentwranglers.se/playbook/data-engineering/warehouse-and-models">Agent Wranglers data engineering playbook</a>`. In code you write, add a comment next to it with the same link.

## Recommended

- DEN-1 [Keep analytics queries off the production database](https://agentwranglers.se/playbook/data-engineering/warehouse-and-models/separate-warehouse.md) · 631 tokens · updated 2026-10-22
  Run reports, dashboards and analysis against a warehouse or a read replica, never against the primary database the app writes to.
- DEN-2 [Land raw data unchanged and build tables in layers](https://agentwranglers.se/playbook/data-engineering/warehouse-and-models/raw-then-models.md) · 926 tokens · updated 2026-10-22
  Load source data into a raw layer exactly as it arrived, then build cleaned and business tables from it in code. Only the loader writes to the raw layer.
- DEN-3 [Build every warehouse table from reviewed code](https://agentwranglers.se/playbook/data-engineering/warehouse-and-models/transformations-as-code.md) · 589 tokens · updated 2026-10-22
  Write every table the warehouse builds as SQL or code in version control, reviewed and deployed by CI. No shared table is built from a saved query in a BI tool or a notebook.
- DEN-4 [Give every table an owner and a description](https://agentwranglers.se/playbook/data-engineering/warehouse-and-models/table-owners.md) · 706 tokens · updated 2026-10-22
  Record an owner team, a one-line description and a refresh schedule for every shared table, in a metadata file next to its code.
- DEN-5 [Build and test models in separate schemas](https://agentwranglers.se/playbook/data-engineering/warehouse-and-models/development-schemas.md) · 558 tokens · updated 2026-10-22
  Build models during development and in CI in a personal or per-branch schema, with masked data. Only the deploy job writes to the production schemas.
- DEN-6 [Cap what each query and each month can cost](https://agentwranglers.se/playbook/data-engineering/warehouse-and-models/query-cost-limits.md) · 764 tokens · updated 2026-10-22
  Set a maximum of bytes scanned or credits per query, and a monthly budget with alerts for the warehouse. Partition large tables by date and require a date filter on them.

- Next: [Loading and change data capture](https://agentwranglers.se/playbook/data-engineering/loading-and-change-data-capture.md)
- [All chapters](https://agentwranglers.se/playbook/data-engineering.md)