# aws-data-analytics

An AWS plugin that gives Claude skills for data lakes, catalogs and ETL work on Amazon services.

- plugin · `type=plugin` · Claude Code · ★ 3282
- Author: Amazon Web Services
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/aws/agent-toolkit-for-aws/tree/HEAD/plugins/aws-data-analytics
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/plugins/aws-data-analytics

## What it does

The plugin bundles 17 skills covering AWS Analytics engineering. You get managed Iceberg tables on Amazon S3 Tables, ingestion from S3 files, JDBC databases, Snowflake, BigQuery, DynamoDB and AWS Glue Data Catalog tables, plus Athena SQL across default and federated catalogs. Other skills handle catalog inventory, business metadata in Amazon SageMaker Catalog, vector embeddings in Amazon S3 Vectors and AWS Glue connections to external sources.

Streaming and orchestration are covered too. Amazon MSK Provisioned clusters, assessing a self-managed Kafka cluster for MSK Express, Apache Flink on Amazon Managed Service for Apache Flink. For workflows there are skills to author, test, debug and upgrade Amazon MWAA DAGs, including Airflow 2.x to 3.x. A Redshift skill walks through the SQL dialect, system views and Data API patterns while correcting mistakes agents usually make.

Everything runs against your real AWS account, so credentials and region have to be in place before the skills do anything useful. Worth checking your IAM profile can touch S3 Tables, Glue and Athena first. Otherwise the calls just fail.

## Requirements
- Works with: AWS

## Install

### Claude Code (native platform)

**Plugin marketplace**
In the agent chat (not a shell):
```text
/plugin install aws-data-analytics@claude-plugins-official
```
In the agent chat (not a shell):
```text
/plugin marketplace add anthropics/claude-plugins-community
```
In the agent chat (not a shell):
```text
/plugin install aws-data-analytics@claude-community
```
In the agent chat (not a shell):
```text
/plugin marketplace add anthropics/claude-plugins-official
```

## When to use it
- create a managed Iceberg table on Amazon S3 Tables
- load data from a JDBC database or DynamoDB into the lake
- run Athena SQL against a federated catalog
- find an asset in AWS Glue Data Catalog by column or S3 path
- diagnose a failed Amazon MWAA DAG run

## Example prompts
- create an Iceberg table in S3 Tables for our events
- ingest data from PostgreSQL into the lake with AWS Glue
- why did the last MWAA DAG run fail

## Source text · aws-data-analytics · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 9b68acc775c280ae.

BEGIN THIRD-PARTY FILE 9b68acc775c280ae
```text
# aws-data-analytics

## Overview

This plugin brings AWS data engineering expertise directly into your coding assistant, covering the full data lifecycle across [AWS Analytics](https://aws.amazon.com/big-data/datalakes-and-analytics/) services; currently, skills are provided to assist with the following capability areas:

- **Data Lake Operations** — Build and operate a data lake on AWS: create managed Iceberg tables on Amazon S3 Tables, ingest data from diverse sources (S3, JDBC databases, Snowflake, BigQuery, DynamoDB, AWS Glue catalog tables), and query across default and federated catalogs with Amazon Athena.
- **Data Discovery** — Inventory and audit your AWS Glue Data Catalog across S3 Tables, Amazon Redshift-federated, and remote Iceberg catalogs. Resolve data asset references by name, keyword, column, or reverse-lookup from S3 location metadata in the catalog.
- **Data Governance (Amazon SageMaker Catalog)** — Curate business metadata in Amazon SageMaker Catalog or the AWS Glue Data Catalog (descriptions, READMEs, glossaries, metadata forms, publishing, and safe asset retirement), and request, approve, share, audit, and revoke access to catalog assets through subscriptions.
- **Vector Storage** — Store and query vector embeddings using Amazon S3 Vectors for cost-effective semantic search and RAG workloads.
- **External Connectivity** — Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, and BigQuery.
- **Search & Observability (OpenSearch)** — Migrate from Solr/Elasticsearch/self-managed OpenSearch into Amazon OpenSearch Service or Serverless, provision domains and collections, and build vector/semantic/hybrid search, log analytics, and trace analytics.
- **Data Warehouse (Amazon Redshift)** — Write Redshift SQL on a provisioned cluster or Serverless workgroup: DDL and distribution/sort keys, COPY/UNLOAD, system views, and the Data API.
- **Workflow Orchestration (Amazon MWAA)** — Author, test, and debug Apache Airflow DAGs on Amazon Managed Workflows for Apache Airflow (MWAA) provisioned environments and YAML workflows on MWAA Serverless, and upgrade provisioned environments to newer Airflow versions, including 2.x to 3.x.
- **Streaming (Amazon MSK)** — Operate Amazon MSK Provisioned clusters with Standard and Express brokers: size and cost a cluster, troubleshoot performance and consumer lag, manage topics, replicate across clusters with MSK Replicator for disaster recovery and active-active topologies, and deliver topic data to Apache Iceberg tables on S3 Tables with Streaming Tables. Plan and execute a migration from self-managed Apache Kafka to MSK Express.
- **Stream Processing (Amazon Managed Service for Apache Flink)** — Develop, deploy, and tune Apache Flink applications on Amazon Managed Service for Apache Flink, including checkpointing, state, connectors, dependency management, and Flink 1.x to 2.x migration.

## Agent Skills

| # | Skill | Description | Documentation |
| -- | -------------------------- | ------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------- |
| 1 | `creating-data-lake-table` | Create managed Iceberg tables using Amazon S3 Tables with automatic compaction, AWS Glue catalog registration, and partitioning | [SKILL.md](skills/creating-data-lake-table/SKILL.md) |
| 2 | `ingesting-into-data-lake` | Import data from S3 files, JDBC databases, Snowflake, BigQuery, DynamoDB, or existing AWS Glue catalog tables into S3 Tables or standard Iceberg | [SKILL.md](skills/ingesting-into-data-lake/SKILL.md) |
| 3 | `querying-data-lake` | Execute and manage Athena SQL queries across default and federated catalogs (AWS Glue, S3 Tables, Amazon Redshift) | [SKILL.md](skills/querying-data-lake/SKILL.md) |
```
END THIRD-PARTY FILE 9b68acc775c280ae

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