AWS Security Blog
Generative AI and machine learning workloads create massive amounts of data. Organizations need data governance to manage this growth and stay compliant. While data governance isn’t a new concept, recent studies highlight a concerning gap: a Gartner study of 300 IT executives revealed that only 60% of organizations have implemented a data governance strategy, with 40% still in planning stages or uncertain where to begin. Furthermore, a 2024 MIT CDOIQ survey of 250 chief data officers (CDOs) found that only 45% identify data governance as a top priority.
Although most businesses recognize the importance of data governance strategies, regular evaluation is important to ensure these strategies evolve with changing business needs, industry requirements, and emerging technologies. In this post, we show you a practical, automation-first approach to implementing data governance on Amazon Web Services (AWS) through a strategic and architectural guide—whether you’re starting at the beginning or improving an existing framework.
In this two-part series, we explore how to build a data governance framework on AWS that’s both practical and scalable. Our approach aligns with what AWS has identified as the core benefits of data governance:
- Classify data consistently and automate controls to improve quality
- Give teams secure access to the data they need
- Monitor compliance automatically and catch issues early
In this post, we cover strategy, classification framework, and tagging governance—the foundation you need to get started. If you don’t already have a governance strategy, we provide a high-level overview of AWS tools and services to help you get started. If you have a data governance strategy, the information in this post can assist you in evaluating its effectiveness and understanding how data governance is evolving with new technologies.
In Part 2, we explore the technical architecture and implementation patterns with conceptual code examples, and throughout both parts, you’ll find links to production-ready AWS resources for detailed implementation.
Before implementing data governance on AWS, you need the right AWS setup and buy-in from your teams.