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

This article explores data governance at scale using Amazon DataZone, focusing on establishing a comprehensive data management strategy for machine learning workflows across multiple accounts.

• Addresses traditional data management challenges like asset discovery, policy enforcement, and data lineage
• Introduces a use case from financial services demonstrating how banks can use governed customer data for targeted marketing
• Describes a multi-account ML platform architecture with dedicated accounts for management, governance, data lakes, and data science
• Highlights Amazon DataZone's capabilities in:
  • Automatic data asset discovery
  • Consistent governance policy enforcement
  • Secure data sharing with fine-grained access controls
• Emphasizes the importance of data governance in maintaining compliance, security, and enabling collaborative data usage

The solution provides a scalable approach to data management, enabling organizations to unlock their data's potential while maintaining robust security and governance standards.