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Querying AWS Sagemaker Catalog

AWSOfficialPublished by AWS

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
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From the author

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.
— the description by AWS

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides guidance and SQL patterns for querying SageMaker Catalog asset metadata exported as Apache Iceberg tables in S3 Tables. It enables users to perform governance audits, track asset growth, identify metadata gaps, and conduct historical comparisons of catalog state without requiring custom ETL pipelines. The skill covers configuration, permission management via Lake Formation, and specific SQL query structures for analyzing catalog inventory.

What it does

  • Provides SQL templates for analyzing catalog asset inventory and metadata.
  • Explains how to enable and configure daily metadata exports from SageMaker Catalog.
  • Details the schema and key columns for querying asset metadata tables.
  • Demonstrates how to perform time-travel analysis to compare catalog snapshots.
  • Outlines required Lake Formation permissions for secure access to catalog data.
  • Offers troubleshooting steps for common configuration and query errors.

When to use it

  • When you need to perform governance queries on your data catalog.
  • When auditing data ownership or identifying assets missing business descriptions.
  • When tracking the growth of cataloged assets over time.
  • When comparing the state of the catalog across different dates.
  • When analyzing catalog metadata for quality or consistency.

Advantages

  • Enables SQL-based analytics on catalog metadata without building custom ETL.
  • Supports historical trend analysis through daily snapshot partitioning.
  • Integrates with standard AWS analytics services like Athena.
  • Provides clear patterns for filtering and joining catalog data.

Usage examples

“How many assets are in my catalog by type?”
Returns a count of assets grouped by resource type using the current daily snapshot.
“Find all assets that are missing a business description.”
Generates a list of assets where the business_description field is NULL.
“Show me the asset growth over the last 30 days.”
Provides a daily count of assets for the past month to visualize catalog growth.
“Compare current catalog descriptions with those from a week ago.”
Performs a join between two snapshots to identify assets that received new descriptions.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/aws/querying-aws-sagemaker-catalog/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip querying-aws-sagemaker-catalog.zip -d .agents/skills

Documentation by AWS

Query AWS SageMaker Catalog System Tables

Overview

Works best with the AWS MCP server 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.

Decision Tree

User intentUse this skill?Alternative
SQL analytics on catalog state (counts, governance, trends)Yes—
Historical comparison ("what changed in catalog last week")Yes — time travel via snapshot_time—
Find assets without owners or descriptionsYes—
Find a specific table by name or conceptNofinding-data-lake-assets or Glue Discovery search
Browse/enumerate catalog interactivelyNoexploring-data-catalog
Run a query on a table's dataNoquerying-data-lake
Manage catalog metadata (add descriptions, tags)NoGlue Discovery put-form-type / associate-glossary-terms

Common Tasks

1. Check If Configured
aws datazone get-data-export-configuration \
  --domain-identifier <DOMAIN_ID> \
  --region <REGION>
  • If no domain exists: aws datazone list-domains --region <REGION>

  • If export not enabled: guide user to enable.

  • One domain per account per region.

Verify table bucket exists:

aws s3tables list-table-buckets --region <REGION> \
  --query "tableBuckets[?name=='aws-sagemaker-catalog']"
2. Enable

With KMS encryption (recommended for production):

aws datazone put-data-export-configuration \
  --domain-identifier <DOMAIN_ID> \
  --region <REGION> \
  --enable-export \
  --encryption-configuration kmsKeyArn=<KMS_KEY_ARN>,sseAlgorithm=aws:kms

Note: Encryption cannot be changed after creation. Always specify KMS for sensitive catalog data.

Without encryption (for quick testing only):

aws datazone put-data-export-configuration \
  --domain-identifier <DOMAIN_ID> \
  --region <REGION> \
  --enable-export

First data available within 24 hours. See: Exporting asset metadata

3. Verify Permissions for Querying

Requires:

  • S3 Tables federated catalog registered in Glue (s3tablescatalog)

  • Lake Formation SELECT + DESCRIBE grants on the table

Grant access:

aws lakeformation grant-permissions \
  --principal DataLakePrincipalIdentifier=<ROLE_ARN> \
  --resource '{"Table": {"CatalogId": "<ACCOUNT>:s3tablescatalog/aws-sagemaker-catalog", "DatabaseName": "asset_metadata", "Name": "asset"}}' \
  --permissions DESCRIBE SELECT \
  --region <REGION>
4. Query

Query syntax:

"s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"

Constraints:

  • You MUST always filter by snapshot_time — without it, the query scans all historical snapshots and returns duplicates

  • You MUST confirm workgroup and output location before executing

  • Default to DATE(snapshot_time) = CURRENT_DATE for current state

  • You SHOULD use the key columns documented in this skill to build queries. If you need the full schema, run get-tables once:

    aws glue get-tables --catalog-id "<ACCOUNT>:s3tablescatalog/aws-sagemaker-catalog" --database-name "asset_metadata" --region <REGION>

Key columns:

ColumnWhat it holdsUsage
snapshot_timePartition key — daily snapshot timestampAlways filter on this
asset_idUnique catalog asset identifierPrimary key for lookups
resource_type_enumGlueTable, RedshiftTable, S3Collection, etc.Filter by asset type
resource_idARN or native identifierCross-reference with source systems
asset_nameBusiness-friendly nameDisplay, search
resource_nameTechnical name (table name, prefix)Filtering
business_descriptionBusiness context (NULL if not provided)Governance gaps
extended_metadatamap<string,string> — flexible key-value attributesUse bracket notation: extended_metadata['owningEntityId']
asset_created_timeWhen asset first appeared in catalogGrowth analysis
asset_updated_timeLast modification timeFreshness checks

Current catalog state:

SELECT resource_type_enum, COUNT(*) as count
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
GROUP BY resource_type_enum
ORDER BY count DESC;

Assets without business descriptions:

SELECT asset_name, resource_name, resource_type_enum, account_id
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
  AND business_description IS NULL;

Asset growth over last 30 days:

SELECT DATE(snapshot_time) as date, COUNT(*) as total_assets
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) >= CURRENT_DATE - INTERVAL '30' DAY
GROUP BY DATE(snapshot_time)
ORDER BY date DESC;

Time travel — compare current vs 7 days ago (new descriptions added):

SELECT t.asset_id, t.resource_name,
       p.business_description as before,
       t.business_description as now
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset" t
JOIN "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset" p
  ON t.asset_id = p.asset_id
WHERE DATE(t.snapshot_time) = CURRENT_DATE
  AND DATE(p.snapshot_time) = CURRENT_DATE - INTERVAL '7' DAY
  AND p.business_description IS NULL
  AND t.business_description IS NOT NULL;

Assets by owner:

SELECT extended_metadata['owningEntityId'] as owner, COUNT(*) as count
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
  AND extended_metadata['owningEntityId'] IS NOT NULL
GROUP BY extended_metadata['owningEntityId']
ORDER BY count DESC;

Filter by metadata form field:

SELECT *
FROM "s3tablescatalog/aws-sagemaker-catalog"."asset_metadata"."asset"
WHERE DATE(snapshot_time) = CURRENT_DATE
  AND extended_metadata['<metadata-form-name>.<field-name>'] = '<field-value>';

Key Behaviors

  • Daily snapshots — exported around midnight per region

  • Always filter by snapshot_time — without it you get all history (duplicates, slow)

  • One domain per account per region — to switch domains, delete config first

  • No additional charge beyond S3 Tables storage + Athena queries

  • Read-only — to update asset metadata, use Glue Discovery APIs or SageMaker Unified Studio

Troubleshooting

ErrorCauseFix
aws-sagemaker-catalog bucket not foundExport not enabledRun put-data-export-configuration --enable-export
Empty results with CURRENT_DATEFirst export hasn't run yet (takes up to 24h)Wait; try yesterday's date
AccessDenied on queryMissing Lake Formation grantsGrant SELECT + DESCRIBE on the table
CATALOG_NOT_FOUNDS3 Tables not registered in GlueEnable integration: S3 console > Table buckets > Enable integration
Duplicate rows in resultsMissing snapshot_time filterAdd WHERE DATE(snapshot_time) = CURRENT_DATE
extended_metadata key returns NULLKey doesn't exist for that assetCheck available keys: SELECT DISTINCT key FROM ... CROSS JOIN UNNEST(map_keys(extended_metadata)) AS t(key) WHERE DATE(snapshot_time) = CURRENT_DATE
Cannot update export encryptionEncryption set at creation time onlyDelete and recreate export config

Security Considerations

Data sensitivity: Catalog metadata exposes organizational structure including asset names, ownership, account IDs, naming conventions, and internal resource identifiers. Treat query results as sensitive by default.

Encryption at rest: Always enable KMS encryption when creating the export configuration. Encryption cannot be changed after creation. Additionally, configure SSE-KMS on your Athena workgroup output bucket.

Least-privilege access: Grant Lake Formation SELECT + DESCRIBE only on the specific asset_metadata.asset table to roles that need catalog analytics. Avoid granting access to the entire aws-sagemaker-catalog bucket.

Audit trail: Enable CloudTrail logging for DataZone (PutDataExportConfiguration, GetDataExportConfiguration), Athena (StartQueryExecution, GetQueryResults), and S3 Tables API calls to track who queries catalog metadata.

Credential hygiene: Use IAM roles with temporary credentials for querying. Avoid long-lived access keys for users accessing catalog metadata. Scope down or rotate principals when access is no longer needed.

Additional Resources

Files

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Requirements and compatibility

Written for: Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter, Needs an MCP server, Needs a command-line tool

Security

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Attribution and licence

Published by
AWS
Publisher
AWS (Official)
Source
aws/agent-toolkit-for-aws · skills/specialized-skills/system-table-skills/querying-aws-sagemaker-catalog · commit 0a218f8
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • NOTICE (added by AutoGineer from NOTICE)
  • ATTRIBUTION.md (written by AutoGineer)
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