The analytics decision
Model scheduled units, collection results, answers, brand observations, citations, prompts, projects, platforms, and page owners as separate entities.
Build the data contract
- Define primary keys and event timestamps before the first load
- Use append-only raw tables for snapshots and citations
- Store success, failure, exclusion, and missing states explicitly
- Version brand aliases, prompt groups, and metric formulas
- Reconcile warehouse counts with the source product on every load
Example data flow
A coverage table should be reproducible from successful observations and brand facts. If the source only exports a percentage, analysts cannot audit denominator changes.
Evidence to retain for AI search data warehouse integration
Keep these fields with the decision:
- source object
- stable key
- time grain
- metric definition
- missing-data state
- transformation
- reconciliation
- owner
Limits and UnderAI's role in AI search data warehouse integration
Warehouse access does not improve source data quality by itself. Extraction gaps and unsupported fields remain gaps after loading.
UnderAI's domain model offers useful entity boundaries, but a public API or export contract is not verified and must be confirmed before architecture is finalized.