Supply chain data is collected from multiple data sources across the enterprise, including ERP/CRM SaaS applications, manufacturing shop-floor edge devices, logs, streaming media, and social networks. Based on the type of data source, AWS Database Migration Service, AWS DataSync, Amazon Kinesis, Amazon Managed Streaming for Apache Kafka, AWS IoT Core, and Amazon AppFlow are used to ingest the data into supply chain data lake in AWS. AWS Data Exchange is used for integrating third-party data into the supply chain data lake, (such as weather data) that may be useful in predicting shipment ETA. AWS Lake Formation is used to build the scalable supply chain data lake. Amazon Simple Storage Service (Amazon S3) is used for supply chain data lake storage. AWS Glue is used to extract, transform, catalog, and ingest data across multiple data stores like ERP, planning, and shipment visibility systems. Amazon Athena is a serverless interactive query service used to analyze data in Amazon S3 using standard SQL. Amazon QuickSight provides dashboards to help planners drill-down from supply chain planning to execution to real-time shipment status while making business decisions. AmazonRedshift is used as a cloud data warehouse. Amazon EMR provides the cloud big data platform for processing vast amounts of data using open source tools. . Amazon SageMaker and AWS AI services can be used to build, train, and deploy ML models, and add intelligence to your supply chain applications. Amazon Neptune graph database is designed to optimize network queries for speed and accuracy.
