warehousing

DE//AGENT currently lists 6 resources under warehousing: 6 tutorials. Everything below is derived from the live registry — counts, capabilities, verification state and security posture come from the curated records, never from marketing copy.

Documented learning objectives across these resources:

• Name the three numbers that describe a warehouse query — bytes scanned, partitions scanned ratio, queue time — via The warehouse mental model — micro-partitions, clustering, scan vs compute
• Explain why a table is a set of micro-partitions and what a clustering key prunes — via The warehouse mental model — micro-partitions, clustering, scan vs compute
• Separate a scan problem from a compute problem before touching any knob — via The warehouse mental model — micro-partitions, clustering, scan vs compute
• Audit a warehouse project against the model-tests-docs triad — via Capstone — the warehousing checklist, end to end
• Verify layering, grain, incremental lookback, and CI staging on one project — via Capstone — the warehousing checklist, end to end
• Leave a repo whose structure a new joiner can read — via Capstone — the warehousing checklist, end to end
• Confirm a query regression from symptoms and query history — via Incident — the dashboard query that went slow
• Collect the evidence packet — query_id, partitions ratio, bytes, queue split — via Incident — the dashboard query that went slow

10 more objectives live on the individual resource pages.

These resources map to stage: Warehousing (6). Follow the four-phase roadmap to place this topic inside a progression instead of learning it in isolation.

Every entry, its shape and its trust state — sorted by the registry's composite score. This table is the honest version of a marketing comparison: no sponsored placements, no unverifiable claims.

How scores are computed: source quality score.

Highest composite score first:

1. The warehouse mental model — micro-partitions, clustering, scan vs compute score 34.15 — beginner
2. Capstone — the warehousing checklist, end to end score 34.15 — intermediate
3. Incident — the dashboard query that went slow score 34.15 — intermediate

Scores rank provenance, completeness and trust — read how verification works before adopting anything.

Start here if you're new: The warehouse mental model — micro-partitions, clustering, scan vs compute.

Reach for these with production experience: Warehouse production gotchas — cost, full refreshes, late data.

• The warehouse mental model — micro-partitions, clustering, scan vs compute — Build the map before tuning anything: a table is a set of micro-partitions, every query is described by bytes scanned, partitions scanned ratio, and queue time, a clustering key de… details
• Capstone — the warehousing checklist, end to end — Close the series by auditing one warehouse project against everything it taught: models with tests and docs, layered staging to marts with a declared grain, incremental loads with … details
• Incident — the dashboard query that went slow — Run the slow-query runbook as an incident: confirm the regression, split scan cost from compute contention, pull partitions_scanned and bytes from query history as evidence, apply … details
• Make queries prune — clustering keys and scan diagnosis — Choose a clustering key from the predicates of your most expensive queries, prove the prune with partitions_scanned versus partitions_total, and fix the disease you actually have —… details

Adjacent topics: tutorial (6 shared), performance (2 shared), clustering (2 shared).

Study path: the roadmap places this topic in a progression · the scoring model explains the numbers · the trust rule catalog shows every security check these entries passed through.