Automated data discovery: Break free from hours of manual data hunting
summary
Select Star claims automated data discovery cuts manual hunting and boosts productivity up to an 80 percent increase in productivity by scanning warehouses, logs and CSVs to build metadata, popularity scores and example queries. The platform shows table and column popularity, flags ownership, and surfaces that deprecating one table impacts 43 dashboards and 17 tables; it extracts column-level lineage and offers automated ER-style relationship detection (foreign key inference) so teams see what will break before they change pipelines.
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chapters (8)
- 0:00Introduction to data discovery
- 1:26Industry challenges in data discovery
- 5:26Existing solutions and their limits
- 8:21Core parts of data discovery
- 9:29Key features of Select Star
- 12:04Data lineage and usage insights
- 14:10Automated relationship diagrams
- 15:05Key takeaways for tool selection
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