skills.rest
aws
awsOFFICIAL
Explore all skills by this author →
WebsiteGitHub

creating-data-lake-table

Create Iceberg tables in Amazon S3 Tables with schemas and partitioning.

2.3k|234|Updated Apr 23, 2026
Search Tags:#aws#partitioning#iceberg#glue#access-control#data-lake#s3-tables
One-click install
npx skills add https://github.com/aws/agent-toolkit-for-aws --skill creating-data-lake-table-aws
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: creating-data-lake-table
Source: https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/creating-data-lake-table
Command: npx skills add https://github.com/aws/agent-toolkit-for-aws --skill creating-data-lake-table-aws

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Create managed Iceberg tables on Amazon S3 Tables to enable scalable data lake storage with automatic compaction, snapshot management, and catalog integration, reducing manual setup and operational overhead.

Core Features & Use Cases

  • Manage table bucket, namespace, table, and schema with Iceberg-compatible tooling.
  • Enable partitioning, Glue catalog registration, and precise access control for secure, auditable data access.
  • Use case: Create a new analytics table for a streaming or batch workload and make it available to Athena or Iceberg-compatible engines.

Quick Start

Create a new Iceberg table by providing the table name, namespace, bucket, and schema, then verify the table is queryable.

Frequently Asked Questions about creating-data-lake-table

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an Iceberg table on S3 Tables for data lake analytics?▼

To create an Iceberg table on S3 Tables, you must configure the table bucket, namespace, table name, and explicit schema. This automates setup for scalable analytics storage, including catalog integration and snapshot management.

What is the process for setting up Glue catalog integration with S3 Tables?▼

Setting up Glue catalog integration involves registering your S3 Table bucket so Iceberg-compatible engines like Athena can query it. This provides automatic compaction and centralized catalog management for your data lake tables.

Can I apply partitioning strategies and access control to Iceberg tables in S3?▼

Yes, you can apply explicit partitioning strategies and precise access control to Iceberg tables in S3. This ensures secure, auditable data access and optimized query performance for both streaming and batch workloads.

Does this approach work with Athena and other Iceberg-compatible query engines?▼

Yes, S3 Tables with Iceberg format work directly with Athena and other Iceberg-compatible engines. Once you define the schema and register the Glue catalog, the table becomes immediately queryable for analytics workflows.

What are the prerequisites for configuring S3 Table buckets and namespaces?▼

Configuring S3 Table buckets and namespaces requires an AWS environment with appropriate access controls. You need to define the bucket, establish a namespace, and specify an explicit Iceberg schema before table creation.

Related Skills

Explore More Data & Analytics Skills→
mreferremreferre

creating-data-lake-table

Create managed Iceberg tables on Amazon S3 Tables with Glue catalog registration.

Community
Advanced
AndreKuraitAndreKurait

creating-data-lake-table

Automate Iceberg table creation in AWS S3 Tables with IAM access control.

Community
Advanced
AndreKuraitAndreKurait

ingesting-into-data-lake

Ingest data from diverse sources into AWS data lake targets.

Community
Advanced
TeiNamTeiNam
12

aws-lakehouse

Construct and query AWS lakehouses with Apache Iceberg and Amazon Athena.

Community
Advanced