Connecting to S/4 HANA

Configure your SAP S/4 HANA system to turn on ODP-based data extraction through the SAP OData connector for Amazon AppFlow. For more information, see SAP OData connector for Amazon AppFlow.

Configure your SAP data sources or extractors, and generate ODP based OData services for AWS Supply Chain to connect and extract information. For more information, see SAP data sources.

Configure your SAP system with one of the following types of authentication:

Configure security roles in the SAP system to turn on data extraction.

Set up network connectivity to SAP S/4 HANA. If your SAP instance is in a secure VPN and you can't open a port for AWS Supply Chain to connect, we recommend that you use AWS PrivateLink. To manually setup AWS PrivateLink, see AWS for SAP and to automatically setup using AWS CloudFormation, see AWS CloudFormation.

On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake.

On the Data lake page, choose Add New Source.

The Select your supply chain data source page appears.

Choose SAP S/4HANA.

Choose Next.

Under SAP S/4HANA Connection Details, enter the following:

Choose Connect to SAP.

If the SAP username and password are entered correctly, a Connection Successful message appears.

(Optional) Under Optional AppFlow Configuration, Step 1 - Download the JSON template file, choose Download the existing JSON template file to modify the appflow ingestion settings.

After you update the .json file, under Step 2 - Upload the modified JSON template file, choose browse files to upload.

Here is a sample .json file with the required schedule, data flows, and source tables.

{
    "schedule" : { 
        "scheduleExpression"  : "rate(1days)", // scheduleExpression key should be available and the value cannot be null/empty. Format starts with rate and having time values in minutes, hours, or days. For example, rate(1days)
        "scheduleStartTime" : null // Supported format - "yyyy-MM-dd'T'hh:mm:ss[+|-]hh:mm". For example, 2022-04-26T13:00:00-07:00. ScheduleStartTime should atleast be 5 minutes after current time. A null value will automatically set the start time as 5 minutes after the connection creation time
    },
    "dataFlows" : [ // DataFlows cannot be null or empty. Make sure to choose from the list below
        "Company-Company",
        "Geography-Geography",
        "Inventory-Inventory Level",
        "Inventory-Inventory Policy",
        "Outbound-Outbound Order Line",
        "Outbound-Outbound Shipment",
        "Product-Product",
        "Product-Product Hierarchy",
        "Production Order-Inbound Order",
        "Production Order-Inbound Order Line",
        "Purchase Order-Inbound Order",
        "Purchase Order-Inbound Order Line",
        "Purchase Order-Inbound Order Line Schedule",
        "Reference-Reference Fields",
        "Shipment-Shipment",
        "Site-Site",
        "Site-Transportation Lane",
        "Trading Partner-Trading Partner",
        "Transfer Order-Inbound Order Line",
        "Vendor Management-Vendor Lead Time",
        "Vendor Management-Vendor Product",
        "Product-Product UOM"
    ],
    "sourceTables" : [   // sourceTables cannot be empty
        {
            "tableName" : "SomeString", // Should be an existing table name from the SAP instance
            "extractType" : "DELTA",      // Should either be DELTA or FULL 
            "tableCols" : [    // TableCols cannot be empty. Enter valid column names for the table
                "col1",
                "col2",
                "col3"
            ],
            "filters" : [// Optional field
                    "colName" : "col1", // colName value should be part of tableCols
                    "dataType" : "String",  // Should contain values `STRING` or `DATETIME`
                    "value" : "String",
                    "operator" : "String"  // Choose a string value from the pre-defined value of "PROJECTION", "LESS_THAN", "CONTAINS","GREATER_THAN","LESS_THAN_OR_EQUAL_TO","GREATER_THAN_OR_EQUAL_TO","EQUAL_TO","NOT_EQUAL_TO","ADDITION","MULTIPLICATION","DIVISION","SUBTRACTION","MASK_ALL","MASK_FIRST_N","MASK_LAST_N","VALIDATE_NON_NULL","VALIDATE_NON_ZERO","VALIDATE_NON_NEGATIVE",or "VALIDATE_NUMERIC","NO_OP";
            ]
        },
        {

            // sourceTables with same keys - tableName, extractType, tableCols, filters(not mandatory)
        
        }
    ]
}
                

Under Amazon S3 Bucket Billing, review the Amazon S3 billing information, and then select Acknowledge.

Choose Next.

Under Data Mapping, choose Get started.

On the Mapping Recipe page, you can view the default transformation recipe under Field mappings.

Choose Add mapping, to map any additional destination field. The Required Destination Fields are mandatory. Choose Destination field to add an additional custom destination field.

To view the source field values and data mappings from the transformation recipe, you can upload sample data. On the Mapping Recipe page, under Upload sample data, choose browse files, or drag and drop files. The sample data file must contain the required parameters and include the source field names.

Choose Accept all and continue.

Under Review and confirm, you can view the data connection summary. To edit your data field mapping, choose Go back to Data Mapping.

(Optional) Under Recipe Actions, you can do the following:

To review the Amazon S3 location paths where you must upload your SAP source data for ingestion, choose Confirm and configure data ingestion. Alternatively, you can choose Confirm and configure data ingestion later. You can view the data ingestion information anytime. From the AWS Supply Chain dashboard, select Connections. Select the connection dataflow that you want to ingest data, choose the vertical ellipsis, and select Ingestion setup.