[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-656325-105":59,"doc-detail-656325-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","guidance-for-building-a-sap-cloud-data-warehouse-on-aws","Guidance for Building a SAP Cloud Data Warehouse on AWS","","Guidance for building a SAP cloud data warehouse on AWS, using OData protocol extraction from SAP and integrating SAP data with other sources. The reference architecture covers operational data provisioning via SAP Gateway, Amazon AppFlow connectivity through PrivateLink and optional network paths, and extraction to Amazon S3. It then uses AWS Glue for metadata cataloging, loads data into Amazon Redshift using COPY commands, models with SCD2 techniques, and visualizes results in Amazon QuickSight with orchestration via AWS Step Functions and generative BI through Amazon Q.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":30,"@type":76,"position":81},"https://docshare.wps.com/document/technology/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/guidance-for-building-a-sap-cloud-data-warehouse-on-aws/656325/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/guidance-for-building-a-sap-cloud-data-warehouse-on-aws/656325.png","ImageObject",300,407,{"name":92,"@type":93},"Rhys","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-10-25",true,{"@type":102,"interactionType":103,"userInteractionCount":19},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"How is data extracted from SAP in this architecture?","Question",{"text":112,"@type":113},"Configure ODP in the SAP Gateway and create an OData system connection from Amazon AppFlow to the SAP source system. Run the AppFlow flow to extract data and store it in an Amazon S3 bucket.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What AWS services are used to prepare and load the SAP data into the warehouse?",{"text":117,"@type":113},"Use an AWS Glue crawler to create Data Catalog metadata for the extracted S3 data, then load into Amazon Redshift using simple COPY commands. Model the data and integrate other non-SAP sources in the warehouse.",{"name":119,"@type":110,"acceptedAnswer":120},"How are Redshift data mart layers structured and how is history preserved?",{"text":121,"@type":113},"Redshift data mart layers use Slowly Changing Dimension Type 2 (SCD2) modeling to retain full history of data movements. The propagation layer includes SCD2 tables containing change history, and the virtual data mart layer uses materialized views for presentation.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},656325,1792967705,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":29,"category_name":30,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":19,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":81,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":39},687207024643,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Guidance for Building a SAP Cloud Data Warehouse on AWS  \nOverview  \nThis architecture diagram shows how to build a cloud data warehouse on AWS by extracting data from SAP using the OData protocol. You can use the data warehouse to model and combine SAP data with that of other sources loaded into the data warehouse. The next two slides show metadata replication and data marts, respectively.  \n1  \nSAP Enterprise Resource Planning (ERP) system  \nOn AWS, on-premises, or other platform  \nAWS Cloud  \n|  AWS Step Functions workflow \u003Cbr>|  |  |\n| --- | --- | --- |\n| \u003Cbr>3\u003Cbr>\u003Cbr>\u003Cbr>| \u003Cbr>6\u003Cbr>\u003Cbr>\u003Cbr>|  |\n| Amazon AppFlow Amazon S3\u003Cbr>\u003Cbr>AWS Glue\u003Cbr>Data Catalog\u003Cbr>Amazon | Redshift | \u003Cbr>Amazon QuickSight\u003Cbr>|\n\nReviewed for technical accuracy September 11, 2024  \n© 2024, Amazon Web Services, Inc. or its affiliates. All rights reserved.  \nAWS  \nReference Architecture  \nConfigure operational data provisioning (ODP) for extraction in the SAP Gateway of your SAP system.  \nCreate the OData system connection from Amazon AppFlow to your SAP source system. This is through AWS PrivateLink for SAP on AWS. You can connect with AWS through a virtual private network (VPN), AWS Direct Connect , or over the internet.  \nIn Amazon AppFlow , create the flow using the SAP source created in step 2. Run the flow to extract data from SAP and save it to an Amazon Simple Storage Service (Amazon S3) bucket.  \nUse an AWS Glue crawler to create a data catalog entry with metadata for the extracted SAP data in an Amazon S3 bucket.  \nLoad data into Amazon Redshift through simple ‘COPY’ commands. Model the data with other non-SAP sources in your data warehouse.  \nCreate the dataset in Amazon QuickSight with Amazon Redshift as the data source.  \nCreate a dashboard to visualize the business data according to user requirements. Use inbuilt machine learning (ML) and insight features to help enable speed to insight.  \nDeploy AWS Step Functions for overall orchestration and alerting of your data pipelines and processes.  \nThe generative BI capabilities of Amazon Q within Amazon QuickSight offer insights from the data.  \n1  \n2  \n3  \n4  \n5  \n6  \nConfigure ODP for extraction in the SAP Gateway of your SAP system.  \nConfigure and run the SAP Metadata Replication AWS Lambda function.  \nLambda retrieves the SAP credentials from AWS Secrets Manager.  \nLambda reads the config file from Amazon S3 .  \nLambda creates Data Definition Language (DDL) statements and runs them in Amazon Redshift.  \nLambda creates AWS Glue tables in the AWS Glue Data Catalog.  \nGuidance for Building a SAP Cloud Data Warehouse on AWS  \nAmazon Redshift data marts  \nThis architecture diagram illustrates how the Redshift data mart layers are used. With the Slowly Changing Dimension Type 2 (SCD2) data modeling technique, you have the full history of your data movements that you can query.   \n\n| | AWS Cloud\u003Cbr>\u003Cbr>1\u003Cbr>Corporate memory\u003Cbr>\u003Cbr>Amazon S3\u003Cbr>\u003Cbr>S3 IntelligentTiering\u003Cbr>\u003Cbr>Data lake | Operational data store\u003Cbr>\u003Cbr>2\u003Cbr>\u003Cbr>Amazon Redshift\u003Cbr>\u003Cbr>Staging schema (STG) and tables\u003Cbr>\u003Cbr>Template\u003Cbr>Propagation\u003Cbr>\u003Cbr>3\u003Cbr>\u003Cbr>Data Mart (DM) schema SCD2 tables\u003Cbr>\u003Cbr>Template\u003Cbr>Stored procedures\u003Cbr>\u003Cbr>Template\u003Cbr>\u003Cbr>Virtual data mart\u003Cbr>\u003Cbr>4\u003Cbr>\u003Cbr>Architected data mart (ARCHDM) schema and materialized views\u003Cbr>\u003Cbr>Template |\n| --- | --- | --- |\n| \u003Cbr>AWS Glue AWS Glue Data Catalog AWS Step Functions Amazon Athena |  |  |\n\nReviewed for technical accuracy September 11, 2024  \n© 2024, Amazon Web Services, Inc. or its affiliates. All rights reserved.  \nAWS  \nReference Architecture  \nThe corporate memory layer contains all SAP extracted data in Amazon S3 .  \nThe operational data store layer is used to temporarily hold the data until the data is loaded into the Data Mart (DM) and the architected data mart (ARCHDM) layers.  \nThe propagation layer includes the Slowly Changing Dimension Type 2 (SCD2) tables or tables that will contain the entire history of changes.  \nThe virtual data mart layer prov","cbCaioItLTE3lUjK","https://ap.wps.com/l/cbCaioItLTE3lUjK","pdf",133008,"English","# Overview\n## End-to-End Data Pipeline Steps\n## Redshift Data Mart Layers (SCD2)\n## Layer Explanations","[{\"question\":\"How is data extracted from SAP in this architecture?\",\"answer\":\"Configure ODP in the SAP Gateway and create an OData system connection from Amazon AppFlow to the SAP source system. Run the AppFlow flow to extract data and store it in an Amazon S3 bucket.\"},{\"question\":\"What AWS services are used to prepare and load the SAP data into the warehouse?\",\"answer\":\"Use an AWS Glue crawler to create Data Catalog metadata for the extracted S3 data, then load into Amazon Redshift using simple COPY commands. Model the data and integrate other non-SAP sources in the warehouse.\"},{\"question\":\"How are Redshift data mart layers structured and how is history preserved?\",\"answer\":\"Redshift data mart layers use Slowly Changing Dimension Type 2 (SCD2) modeling to retain full history of data movements. The propagation layer includes SCD2 tables containing change history, and the virtual data mart layer uses materialized views for presentation.\"}]","Guidance for Building a SAP Cloud Data Warehouse on AWS | PDF"]