Intelligence · Component · dataset-ingestion-contracts
Reusable B2B signal dataset registration
What it does
Register external signal datasets through validated contracts and normalize public Reddit ingestion for reuse by intelligence workflows.
Core pattern
External dataset contract registration + normalized ingestion
- Input
- Dataset specification and public crawl results
- Output
- Registered dataset metadata and normalized signal records
Key parameters
| Name | Type | Default | Values |
|---|---|---|---|
| operation | string | register | register · validate · ingest · query |
| source_registry | object | — | — |
| extract_schema | — | — | — |
| records | array | [] | — |
| query | — | — | — |
Maturity and limits
Dataset and public-Reddit test files accompany concrete contract/registration services. Phase 2: source paths and implementation inspected statically; tests and external integrations were not executed. Maturity rates repository implementation, not a verified production deployment.
config with credentials present. No root reuse license found; external content/platform terms and internal hotel/business data access constrain reuse.
1 sentence citing source paths or vendor names omitted for publication.
Used in pipelines
Industry tags
- Travel & hotelsSource-supported industry
For work involving destinations, room rates and bookings, use external dataset contract registration followed by normalized ingestion.
- Manufacturing & industryTransferable use
For unified lookup of spare-part catalogs and equipment records, use external dataset contract registration followed by normalized ingestion.
- SportsTransferable use
Support “Register fixture-related sources” with external dataset contract registration followed by normalized ingestion.
- Government & public servicesTransferable use
Support “Register public information sources” with external dataset contract registration followed by normalized ingestion.
Skills pack
Contract scaffold and deterministic mock
Download · 11KBSHA-256 40a4e57ab61969e16031fc4ce87df79481620b61c67e22e2a00df0d4cbe876c8
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