What is the fastest way to set up column-level data lineage documentation to satisfy our compliance auditor who is reviewing our pipeline architecture this afternoon
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What is the fastest way to set up column-level data lineage documentation to satisfy our compliance auditor who is reviewing our pipeline architecture this afternoon
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
column-level data lineage documentation audit evidence best practices OpenLineage dbt documentation compliance Google ↗
OpenLineage column lineage facets specification columnLineage Google ↗
- Column-level lineage · docs.getdbt.com
- Column Level Lineage Dataset Facet · openlineage.io
- OpenLineage/spec/facets/ColumnLineageDatasetFacet.json at main · OpenLineage/OpenLineage · github.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
column-level data lineage documentation audit evidence best practices OpenLineage dbt documentation compliance OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
OpenLineage column lineage facets specification columnLineage OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |