This article explains how to implement data mesh architecture on AWS to modernize data platforms and accelerate innovation while maintaining proper governance.

• Data mesh decentralizes data ownership by business domain instead of centralizing in IT
• Common failures include lack of coordination between domain teams and enterprise data teams
• Enterprise should manage raw data lakes and conformed data warehouses; domains manage consumption layers
• Data governance should be provided as a service to facilitate domain-specific data products
• AWS services: Amazon DataZone, AWS Lake Formation, AWS Glue, Amazon Redshift, Amazon S3
• Healthcare customer developed 14 predictive models in 8 weeks using data mesh approach
• Pharmaceutical company eliminated analytics backlog by establishing domain ownership with central governance
• Key principles: domain ownership, federated governance, data as product, self-serve sharing

Successful data mesh requires balancing enterprise data management with domain autonomy using AWS managed services for integration, preparation, and data serving.