Data lake - AWS Supply Chain

Data lake

You can use AWS Supply Chain to ingest your data stored in the following data sources and extract your supply chain information. AWS Supply Chain can store the extracted information in your Amazon S3 buckets and use the data for Demand planning, Insights, Supply Planning, N-Tier Visibility, Work Order Insights, and Sustainability.

  • Amazon S3 source data – You can use the Amazon S3 data source flow option if you don't have an ERP system, or if you use another extraction tool. You can extract raw data from your data source, map the data fields with AWS Supply Chain data model, and upload them to Amazon S3 with an integration tool of your choice. You can only upload CSV files to Amazon S3 when you're using Auto-association.

  • Electronic data interchange (EDI) – AWS Supply Chain supports X12 ANSI version 4010 for EDI messages 850, 860, and 856. Supported data formats are .edi or .txt. You can add your raw EDI messages to Amazon S3 using an integration tool of your choice. AWS Supply Chain can extract and associate your raw EDI messages using default templates by Natural Language Processing (NLP) for EDI 856. NLP templates are not supported for EDI 850 and 860 and come with pre-defined, but customizable recipes in AWS Supply Chain.

  • SAP S/4HANA – To extract your supply chain data from an SAP S/4HANA data source, AWS Supply Chain can use the Amazon AppFlow connector to connect to this source. AWS Supply Chain can associate your supply chain data stored in SAP S/4HANA system to the AWS Supply Chain data model using AWS Glue DataBrew.

  • SAP ECC 6.0 – You can use an integration tool (for example, ETL or iPaaS) to extract your supply chain data stored in the SAP ECC 6.0 system and put it into the Amazon S3 bucket using an API. AWS Supply Chain can associate your supply chain data stored in the SAP ECC 6.0 system to the AWS Supply Chain data model using DataBrew.

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