SCSUS05-BP01 Adopt modern data management and governance practices for your supply chain sustainability, and focus on economic, environmental, and social needs

Consider supply chain fine-tuned data lake, analytics, and data governance practices with specific focus on sustainability to address economic, environmental and social needs.

Desired outcome: Implement robust data management practices to help with sustainability-related use cases, providing support for accurate, secure, and comprehensive datasets.

Level of risk exposed if this best practice is not established: High

Implementation guidance

Consider the adoption of a managed supply chain fine-tuned data lake using Amazon S3, and Amazon S3 Tables and table bucket, for unmatched performance, durability, availability, scalability, security, compliance and audit capabilities, in combination with AWS Lake Formation to accelerate the build of secure data lakes. Build your data inventory considering all the data sources (both internal and external), your EDI flows, and create your data catalog with the proper metadata and tags that can help you map which information is contributing to both the economic, environmental and social needs perspectives.

Implementation steps

1. Implement a managed supply chain data lake using Amazon S3, Amazon S3 Tables and table buckets, and AWS Lake Formation to centralize sustainability-related data.

2. Build a comprehensive data inventory that includes internal and external data sources, EDI flows, and sustainability metrics.

3. Create detailed data catalogs with metadata and tags that map data contributions to economic, environmental, and social sustainability needs.

4. Implement data governance policies and access controls to maintain data quality and security across the sustainability data environment.

5. Establish data integration pipelines that connect AWS Glue with Amazon DataZone for comprehensive data management across organizational boundaries.