finding-data-lake-assets

You can resolve ambiguous data lake assets by providing a table name, keyword, column name, or S3 path. The Skill searches the Glue Data Catalog first, then uses S3 reverse lookup or Redshift if needed, stopping early on the first high-confidence match to return the concrete table reference and location.

Resolving data lake table references is handled by searching Glue Data Catalog, S3, S3 Tables, and Redshift in a layered sequence. It returns the resolved table reference with format and location, while always reporting both the sources searched and the sources skipped.

Yes, you can provide an S3 path to perform a reverse lookup. The Skill checks the Glue Data Catalog first for high-confidence matches and uses S3 reverse lookup when appropriate to identify the underlying table reference.

Yes, an AWS region is required for resolution. The Skill automatically prompts you for the missing AWS region before proceeding with the metadata lookup across Glue, S3, S3 Tables, and Redshift.

When data lake asset searches yield weak or absent results, the Skill employs confidence-gated disambiguation. It lists the top candidate matches for medium confidence and transparently reports all sources searched and skipped, ensuring you know what was checked.

Resolving data lake tables uses layered discovery with early stopping to minimize latency and token usage. It searches Glue first for high-confidence matches and only queries S3 reverse lookup or Redshift when appropriate, avoiding unnecessary catalog scans.