AI Models & Assistants / Knowledge library
AWS Data Analytics (ChatGPT plugin)
Data lake, analytics, and ETL workflows with S3 Tables, AWS Glue, and Athena. Covers managed Iceberg tables on S3 Tables, ingestion from JDBC databases, Amazon Redshift, Snowflake, BigQuery, and DynamoDB, AWS Glue Data Catalog inventory and asset discovery, federated Athena queries, and vector storage and semantic search on Amazon S3 Vectors.
Why learn AWS Data Analytics (ChatGPT plugin)?
Brings AWS Data Analytics capabilities into ChatGPT so the assistant can work with that service's context.
The problem it solves
Reduces manual handoffs between ChatGPT and AWS Data Analytics.
Where it came from
AWS Data Analytics (ChatGPT plugin): Data lake, analytics, and ETL workflows with S3 Tables, AWS Glue, and Athena. Covers managed Iceberg tables on S3 Tables, ingestion from JDBC databases, Amazon Redshift, Snowflake, BigQuery, and DynamoDB, AWS Glue Data Catalog inventory and asset discovery, federated Athena queries, and vector storage and semantic search on Amazon S3 Vectors. Directory record checked 2026-10-12. Availability depends on region, plan, permissions and the publisher. Directory presence does not establish a quality ranking.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Explain what AWS Data Analytics (ChatGPT plugin) does.
- Identify a use case for AWS Data Analytics (ChatGPT plugin).
- Describe a limitation of AWS Data Analytics (ChatGPT plugin).
- Name a compatible tool for AWS Data Analytics (ChatGPT plugin).
- Compare AWS Data Analytics (ChatGPT plugin) against an alternative.
Documentation and sources
- Primary source / model card (chatgpt.com)
Catalog research notes
- See the AI Workbench for source dates, pricing evidence and configuration details.