Can I use this for real-time data streaming?

While it focuses on data lake patterns, it provides event-driven Lambda patterns suitable for processing data as it arrives in S3.

How does the data-aws skill help with AWS cost management?

It enforces strict partitioning strategies and right-sizing of compute resources, preventing expensive full table scans in Athena and over-provisioned Glue jobs.

Which AWS services are primarily supported?

The skill includes specialized patterns for S3, Glue, Lambda, Athena, Redshift, and Step Functions orchestration.

Does this skill support Infrastructure as Code (IaC)?

This skill focuses on implementation patterns and architectural logic; infrastructure provisioning via Terraform or CDK is deferred to the data-iac skill.

AWS Data Architect

Name: AWS Data Architect
Author: AlexanderStephenThompson

byAlexanderStephenThompson

클라우드 인프라

Implements best-practice data engineering patterns and architectures across AWS services like S3, Glue, and Athena.

소개

The data-aws skill equips Claude with standardized patterns for building scalable AWS data solutions, focusing on S3 data lake foundations, efficient partitioning, and event-driven processing. It provides structured guidance for Glue ETL jobs, Athena query optimization through partition projection, and Lambda-based data processing, ensuring that data pipelines are cost-effective, high-performing, and follow AWS architectural best practices. It is particularly useful for engineers transitioning from monolithic databases to cloud-native distributed data architectures.

주요 기능

Athena partition projection and SQL query performance optimization
Step Functions orchestration for multi-stage data pipelines
Glue ETL job configuration and Redshift distribution/sort key tuning
0 GitHub stars
Optimized S3 data lake path structuring and tiered storage patterns
Lambda-based event-driven data transformation and processing

사용 사례

Automating ETL processes using AWS Lambda triggered by S3 object events
Optimizing Athena query performance and reducing costs via partition projection
Designing a scalable S3 data lake with standardized multi-tier partitioning

소개

주요 기능

Athena partition projection and SQL query performance optimization
Step Functions orchestration for multi-stage data pipelines
Glue ETL job configuration and Redshift distribution/sort key tuning
0 GitHub stars
Optimized S3 data lake path structuring and tiered storage patterns
Lambda-based event-driven data transformation and processing

사용 사례

Automating ETL processes using AWS Lambda triggered by S3 object events
Optimizing Athena query performance and reducing costs via partition projection
Designing a scalable S3 data lake with standardized multi-tier partitioning