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SCCOST02-BP01 Have a plan for your raw data storage to optimize cost - Supply Chain Lens
Implementation guidance

SCCOST02-BP01 Have a plan for your raw data storage to optimize cost

Effective data management strategies can substantially lower expenses related to maintaining vast data volumes. Object storage is recommended for large-scale unstructured data due to its robustness, nearly unlimited capacity, scalability, and advanced metadata capabilities.

Desired outcome: A well-defined data storage strategy for the vast amount of structured or unstructured data generated by SCM systems which is cost-efficient and aligned with business requirements.

Benefits of establishing this best practice: Reduced cost, optimized performance, and improved customer satisfaction.

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

Implementation guidance

Implement object storage with appropriate storage classes to manage voluminous supply chain data efficiently, using Amazon S3 Standard for frequently accessed data, Amazon Glacier for archiving, and S3 Intelligent-Tiering for dynamic allocation based on usage patterns.

Employ schema-on-read services like Amazon Athena to query data in its original format, reducing storage costs, and implement data lifecycle policies to automate transitions between storage classes.

Implementation steps

  1. Analyze data access patterns and classify supply chain data based on frequency of access and business criticality.

  2. Implement appropriate Amazon S3 storage classes for different data types, optimizing costs based on access patterns.

  3. Configure S3 Intelligent-Tiering for data with changing or unknown access patterns to automatically optimize storage costs.

  4. Deploy Amazon Athena for cost-effective querying of data in its original format without requiring data transformation.

  5. Establish automated data lifecycle policies to transition data between storage classes and archive or delete obsolete data.

  6. Monitor storage costs and usage patterns regularly to identify additional optimization opportunities.