What problem does it solve? Data teams need visibility into their SageMaker Catalog inventory—asset counts, governance gaps, ownership, and historical changes—without building custom ETL pipelines. This Skill enables direct SQL analytics over the daily-snapshot Apache Iceberg table that SageMaker Unified Studio exports to S3 Tables. ## Core Features & Use Cases - Catalog Inventory Analytics: Count assets by type, track growth over time, and audit ownership using Athena SQL against the asset_metadata.asset table. - Governance & Quality Audits: Find assets missing business descriptions, filter by metadata form fields, and identify undocumented resources. - Time-Travel Comparisons: Compare catalog snapshots across dates to detect what changed, such as newly added descriptions or new assets. - Setup & Permissions Guidance: Covers enabling the DataZone export configuration, verifying the S3 table bucket, and granting Lake Formation SELECT/DESCRIBE permissions. - Use Case: A data governance lead asks "which assets have no owner?" and gets a SQL query grouping assets by extended_metadata['owningEntityId'] filtered to the current snapshot. ## Quick Start Ask the assistant to show how many assets of each type exist in the SageMaker Catalog today, and it will generate and run the appropriate Athena SQL query filtered by the current snapshot_time.
