Implementing Data Governance in AWS: Automation, Tagging, and Lifecycle Strategies – Part 1 | Amazon Web Services

AWS Database Blog’s first of a two-part series, translated and edited in Korean, introduces a practical framework for implementing data governance on AWS.

It recommends preparing governance with AWS Organizations, CloudTrail, Config, IAM, and clear role definitions, compliance requirements, and change management planning.

The post highlights key metrics such as tag compliance, response time, reduced manual work, and lower storage costs.

It also summarizes the AWS services used for governance, including automation, monitoring, sensitive data discovery, and lifecycle policies.

The approach aims to improve compliance and cost optimization for growing data workloads driven by generative AI and machine learning.