Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. To view this series from the beginning, start with Part 1. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. The data mesh is a modern approach to data management that decentralizes data ownership and treats data as a product. It enables different business units within an organization to create, share, and govern their own data assets, promoting self-service analytics and reducing the time required to convert data experiments into production-ready applications. The data mesh architecture aims to increase the return on investments in data teams, processes, and technology, ultimately driving business value through innovative analytics and ML projects across the enterprise.

Organizations spanning various industries are progressively utilizing data and ML to drive innovation, enhance decision-making processes, and gain a competitive ...