Individual skill
querying-aws-sagemaker-catalog
Runs SQL analytics on SageMaker Catalog asset metadata tables exported as Apache Iceberg in S3 Tables. Covers governance queries, asset growth tracking, ownership audits, time-travel over catalog state, and metadata quality analysis. Applies when querying catalog inventory, finding assets without descriptions, comparing catalog snapshots, or auditing data ownership. Trigger phrases: catalog inventory SQL, how many assets, assets without descriptions, asset growth over time, who owns this data, catalog governance, data quality audit, catalog analytics.
skills/specialized-skills/system-table-skills/querying-aws-sagemaker-catalog/SKILL.md
Source commit 1761e96813ebcbd43ed81d19e837219033f0afe5
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- Last checked
- Nov 3, 2026
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- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
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# Query AWS SageMaker Catalog System Tables
## Overview
**Works best with** the [AWS MCP server](https://docs.aws.amazon.com/aws-mcp/) for sandboxed execution and audit logging. All commands below use the AWS CLI and work in any environment with configured AWS credentials.
Amazon SageMaker Unified Studio (whose catalog feature is referred to below as SageMaker Catalog) exports asset metadata as a daily-snapshot
Apache Iceberg table in the AWS-managed `aws-sagemaker-catalog` table bucket. This
enables SQL queries over your entire data catalog inventory — asset counts, governance
gaps, ownership audits, and historical comparisons — without building custom ETL.
Data is partitioned by `snapshot_time` and exported once daily (around midnight per
region). The table is read-only.
