Implementing data governance on AWS: Automation, tagging, and lifecycle strategy – Part 2

This document provides a technical, phased approach to implementing data governance on AWS, starting with monitoring baselines and progressing through preventive enforcement, automated remediation, and advanced capabilities. It outlines organization-wide tag policies, multi-account strategies, integration with on-premises frameworks, automated security controls based on classification, data residency and disaster recovery considerations, and compliance monitoring using AWS Config, CloudWatch, and Amazon Macie. It also covers data lakes with the Modern Data Architecture Accelerator, access analytics via CloudTrail and Athena, machine learning model governance with SageMaker, and cost optimization through S3 lifecycle rules, alongside best practices and common implementation challenges.