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pre[class*=language-]{background-color:rgba(var(--ui-12-rgb),.5);color:var(--text-01);text-shadow:none;padding:var(--spacing-00);border-radius:var(--spacing-00);font-size:smaller}",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false},"responsivegrid":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"quickstart_hero":"aem-GridColumn aem-GridColumn--default--12","flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn 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src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/cal.png\" alt=\"cal\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EActivate your Snowflake account:\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/snow.png\" alt=\"Snowflake Account\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EExtract and load Accounts Receivable data through 0fi_ar_4 extractor-->ODP API -->Azure Data Factory to Snowflake, full and delta:\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/df_overview.png\" alt=\"Data flow\"\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EUse pre-built \u003Ca href=\"https://docs.getdbt.com/dbt-cli/cli-overview\"\u003Edbt CLI\u003C/a\u003E data flows to:\n\u003Cul\u003E\u003Cli\u003Etranslate technical field names into business friendly terms\u003C/li\u003E\u003Cli\u003Eperform a currency conversion transform\u003C/li\u003E\u003Cli\u003Ecombine customer master data with accounts documents.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThis is a screen capture of DBT's auto-documentation of the data flow we will create:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/dbt_ar.png\" alt=\"DBT Data Flow\"\u003E\u003C/p\u003E\n","\u003Cp\u003EWe provide a Tableau report to visualize the data regionally, per customer, per DSO, and per document number.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/Account_Receivable_Dasboard_Tableau.png\" alt=\"Tableau Dashboard\"\u003E\nLet’s get started!\u003C/p\u003E\n","\u003Ch3\u003EWhat you need to have before starting the lab\u003C/h3\u003E\n","\u003Cp\u003ETo participate in the virtual hands-on lab, attendees need the following:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAdmin rights to an Azure trial account\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://blogs.sap.com/2020/01/17/creating-a-p-user-in-sap-cloud-platform-to-practise-sap-hana./\"\u003EAn SAP s- or p-user or linked Universal ID\u003C/a\u003E to log on to SAP's Cloud Appliance Library (cal.sap.com).\u003C/li\u003E\u003Cli\u003EA credit card to add billing information to the Azure account\u003C/li\u003E\u003Cli\u003EA Snowflake account with \u003Ccode\u003EACCOUNTADMIN\u003C/code\u003E access (you can get a \u003Ca href=\"https://signup.snowflake.com/?utm_cta=quickstarts_\"\u003Efree Trial account here\u003C/a\u003E)\u003C/li\u003E\u003Cli\u003EFamiliarity with Snowflake and Snowflake objects (eg. through the \u003Ca href=\"/en/developers/guides/getting-started-with-snowflake/\"\u003EZero-To-Snowflake hands-on-lab\u003C/a\u003E)\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://git-scm.com/book/en/v2/Getting-Started-Installing-Git\"\u003Egit\u003C/a\u003E installed on your local machine\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://www.tableau.com/products/desktop/download\"\u003ETableau desktop\u003C/a\u003E installed on your local machine (optional)\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat you will install during the lab\u003C/h3\u003E\n","\u003Cp\u003EYou will install \u003Ca href=\"https://docs.getdbt.com/dbt-cli/install/pip\"\u003Edbt CLI\u003C/a\u003E during the lab.\u003C/p\u003E\n","\u003Cp\u003EThe following will be installed or used in your Azure environment:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ESAP ECC\u003C/li\u003E\u003Cli\u003Ea Windows virtual machine\u003C/li\u003E\u003Cli\u003Ean Azure self-hosted integrated runtime on the virtual machine\u003C/li\u003E\u003Cli\u003EAzure Data Factory\u003C/li\u003E\u003Cli\u003Ean Azure auto resolve integration runtime.\u003C/li\u003E\u003Cli\u003EADLS Gen 2 storage\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EYou will activate your Snowflake account.\u003C/p\u003E\n","\u003Ch3\u003EWhat you will learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to deploye and activate an SAP test machine using SAP Computer Appliance Library.\u003C/li\u003E\u003Cli\u003EHow to use Azure Data Factory to request data from SAP through the ODP API.\u003C/li\u003E\u003Cli\u003EHow to install and run a pipelines using DBT & Snowflake.\u003C/li\u003E\u003Cli\u003EHow to transform SAP data in Snowflake.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat you will build\u003C/h3\u003E\n","\u003Cp\u003EAn Accounts Receivable pipeline for Financial Services from SAP ECC to Snowflake to Tableau.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ECreate Azure account & deploy SAP ERP\u003C/h2\u003E\n","\u003Cp\u003E<aside class="callout">\nIn the interest of getting data out of SAP for this lab, we will use Azure Data Factory's SAP CDC connector, but there are many other ways to do this, and we are not recommending this particular path. If you otherwise have access to the demo data in this lab, you can skip building the Azure and SAP environments and go directly to the sections of creating your Snowflake account and installing and configuring DBT.\n</aside>\u003C/p\u003E\n","\u003Cp\u003EIn this section, we:\ncreate and activate an Azure free-trial environment\naccess SAP Cloud Application Library (SAP CAL), choose a template and deploy:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ESAP ERP 6.0 EHP6\u003C/li\u003E\u003Cli\u003EWindows virtual machine\u003C/li\u003E\u003Cli\u003ESubnets\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E<aside class="callout">\nI use an SAP ECC instance, but you can adapt this quickstart to use an S/4HANA instance.\n</aside>\u003C/p\u003E\n","\u003Cp\u003EFor full documentation on the Azure/SAP setup, check \u003Ca href=\"https://learn.microsoft.com/en-us/azure/data-factory/sap-change-data-capture-introduction-architecture\"\u003Ehere\u003C/a\u003E.\u003C/p\u003E\n","\u003Cp\u003EAlternatively, if you are on AWS, you can adapt from the following AWS lab: \u003Ca href=\"https://catalog.workshops.aws/sap-on-aws-beyond/en-US/01-preparation/60-sap-env\"\u003ESAP on AWS Beyond Lab\u003C/a\u003E.\u003C/p\u003E\n","\u003Cp\u003E<aside class="callout">\nAfter this section you will set up the Snowflake account and Configure ADF. If you wish, you can configure Snowflake first.\n</aside>\u003C/p\u003E\n","\u003Ch3\u003EUse SAP CAL to create SAP ERP\u003C/h3\u003E\n","\u003Cp\u003EPrerequisites:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAdmin rights on an \u003Ca href=\"https://learn.microsoft.com/en-us/training/modules/create-an-azure-account/\"\u003EAzure account\u003C/a\u003E\u003C/li\u003E\u003Cli\u003EAccess to https://cal.sap.com\nUse the \u003Ca href=\"https://www.youtube.com/watch?v=iORePziUMBk\"\u003Ethis video\u003C/a\u003E to set up your Azure account and create an SAP instance in Azure through SAP CAL:\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EAdjust the following resources in Usage + quotas in your Azure subscription, before deploying from SAP CAL.\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ETotal Regional vCPUs to \u003Ccode\u003E50\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EStandard ESv5 Family CPUs to \u003Ccode\u003E10\u003C/code\u003E vCPU.\u003C/li\u003E\u003Cli\u003EStandard DSv5 Family CPUs to \u003Ccode\u003E10\u003C/code\u003E vCPU.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E<aside class="callout">\nIDES trial accounts have data in them, but are limited to 30 days. Development accounts tend not to have data in them, but the developer licenses are renewable.\n</aside>\u003C/p\u003E\n","\u003Cp\u003EDeployment can easily take an \u003Cstrong\u003Ehour\u003C/strong\u003E, so now is a good time to go to the Snowflake section and follow the setup steps. When the instance is activated and Snowflake is configured, come back here and continue.\u003C/p\u003E\n","\u003Ch3\u003ETest access to SAP\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EFrom  cal.sap.com > Appliances, select \u003Cstrong\u003EConnect\u003C/strong\u003E next to your deployed appliance.\u003C/li\u003E\u003Cli\u003EChoose RDP > Connect User name: Administrator, Password is the Master one you entered for the appliance.\u003C/li\u003E\u003Cli\u003EDouble-click the \u003Cstrong\u003ESAP Logon\u003C/strong\u003E icon.\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003ELog On\u003C/strong\u003E:\n\u003Cul\u003E\u003Cli\u003EUser: idadmin,\u003C/li\u003E\u003Cli\u003EPassword: ides123 (or check the Getting Started Guide for the SAP instance)\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E<aside class="callout">\nCheck that you have Accounting >  Financial Accounting > Accounts Receivable in the SAP menu. If you don't you may not have any data, and may have to terminate this instance and launch a new, different instance.\n</aside>\u003C/p\u003E\n","\u003Ch2\u003ECreate & configure Snowflake\u003C/h2\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ESign up for a Snowflake trial account at https://signup.snowflake.com/.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ELogin to your Snowflake trial account.\u003Cbr\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/login_screen.png\" alt=\"Login Screen\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-manager.html#quick-tour-of-the-web-interface\"\u003Ehere\u003C/a\u003E for a quick tour of the Snowflake's user interface, Snowsight.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate a database and a service accounts for dbt. Create a worksheet, copy the below, paste into the worksheet,  change the password and run it.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E<aside class="callout">\nMake sure you change the password before running the script!\n</aside>\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-------------------------------------------\n-- create demo database\n-------------------------------------------\nUSE ROLE accountadmin;\nCREATE DATABASE IF NOT EXISTS sap_demo; \n-------------------------------------------\n-- create virtual warehouse compute cluster\n-------------------------------------------\nUSE ROLE sysadmin;\nCREATE OR REPLACE WAREHOUSE sap_dbt_wh \n  WAREHOUSE_SIZE = 'MEDIUM' \n  AUTO_SUSPEND = 60 \n  AUTO_RESUME = TRUE \n  MIN_CLUSTER_COUNT = 1 \n  MAX_CLUSTER_COUNT = 3 \n  INITIALLY_SUSPENDED = TRUE;\n-------------------------------------------\n-- role and user\n-------------------------------------------\nUSE ROLE securityadmin;\nCREATE OR REPLACE ROLE sap_dbt_role;\n------------------------------------------- Please replace with your dbt user password\nCREATE OR REPLACE USER sap_dbt_user default_role = sap_dbt_role default_warehouse = sap_dbt_wh PASSWORD = "sap_dbt123!";\n-------------------------------------------\n-- Grants\n-------------------------------------------\nGRANT ROLE sap_dbt_role TO USER  sap_dbt_user;\nGRANT ROLE sap_dbt_role TO ROLE sysadmin;\nGRANT ALL ON DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON ALL SCHEMAS IN DATABASE sap_demo  TO ROLE sap_dbt_role;\nGRANT ALL ON ALL TABLES IN DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON FUTURE SCHEMAS IN DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON FUTURE TABLES IN DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON WAREHOUSE sap_dbt_wh TO ROLE sap_dbt_role;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAs result of these steps, you will have:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003Eone empty databases: \u003Ccode\u003Esap_demo\u003C/code\u003E\u003C/li\u003E\u003Cli\u003Eone virtual warehouse: \u003Ccode\u003Esap_dbt_wh\u003C/code\u003E\u003C/li\u003E\u003Cli\u003Eone role and one user: \u003Ccode\u003Esap_dbt_role\u003C/code\u003E and \u003Ccode\u003Esap_dbt_user\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ECreate Azure Data Factory, runtimes & storage\u003C/h2\u003E\n","\u003Cp\u003EIn this section, we will set up:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAzure Data Factory\u003C/li\u003E\u003Cli\u003Ea self-hosted Integrated Run-time (IR) for the SAP to ADF connection\u003C/li\u003E\u003Cli\u003Ean Azure AutoResolveIR to connect to Snowflake\u003C/li\u003E\u003Cli\u003Ean ADLS Gen 2 storage area.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EFor more information on how to use Azure Data Factory, please see \u003Ca href=\"https://learn.microsoft.com/en-us/azure/data-factory/\"\u003Ehere\u003C/a\u003E.\u003C/p\u003E\n","\u003Ch3\u003ECreate Azure Data Factory\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EFrom the remote desktop Windows machine that was deployed by CAL, access https://portal.azure.com/#home and select Data Factories\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003E+ Create\u003C/strong\u003E and fill in the details.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003EWest Europe\u003C/strong\u003E for the region.\u003C/li\u003E\u003Cli\u003EReview + create > Read the Terms > Create.\u003C/li\u003E\u003Cli\u003EThe system creates the Data Factory.\u003C/li\u003E\u003Cli\u003ESelect Go to resource > Launch studio.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate self-hosted integration runtime\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EFrom Data Factory Studio select \u003Cstrong\u003EManage\u003C/strong\u003E from the left (Tool Box icon).\u003C/li\u003E\u003Cli\u003ESelect Integration runtimes > + New > Azure, Self-Hosted > Continue\u003C/li\u003E\u003Cli\u003ESelect Self-Hosted > Continue (yes, again...)\u003C/li\u003E\u003Cli\u003EName it \u003Ccode\u003ESapIR\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003EOption 1: Express setup\u003C/strong\u003E to install the IR on the remote desktop Windows machine\u003C/li\u003E\u003Cli\u003EThe executable downloads onto the remote machine.\u003C/li\u003E\u003Cli\u003EFrom the downloads, right-click on the executable, \u003Cstrong\u003Erun as Administrator\u003C/strong\u003E. The IR installs on the remote machine.\u003C/li\u003E\u003Cli\u003EInstall the \u003Ca href=\"https://support.sap.com/en/product/connectors/msnet.html\"\u003ESAP NCo 3.0\u003C/a\u003E (\u003Ccode\u003Enot 3.1\u003C/code\u003E), with option Install assemblies to GAC.\u003C/li\u003E\u003Cli\u003EBack in Home > Virtual Machines > ERP6... > Networking, add inbound port rule for \u003Ccode\u003E3200\u003C/code\u003E and \u003Ccode\u003E3300\u003C/code\u003E. See \u003Ca href=\"https://learn.microsoft.com/en-us/azure/data-factory/sap-change-data-capture-shir-preparation\"\u003ESetup SHIR\u003C/a\u003E for more detailed information.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate ADLS Gen 2 storage\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EFrom https://portal.azure.com/#home > Storage, select + Create.\u003C/li\u003E\u003Cli\u003EName it \u003Ccode\u003Eazurestage\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EAssign it to your subscription, sap resource group, and West Europe Region, with Standard performance, and Locally-redundant storage.\u003C/li\u003E\u003Cli\u003ESelect Create. Azure deploys the storage.\u003C/li\u003E\u003Cli\u003EGo to Azure > Storage > \u003Ccode\u003Eazurestage\u003C/code\u003E > Data Protection, and turn \u003Cem\u003Eoff\u003C/em\u003E \u003Cstrong\u003EEnable soft delete for blobs\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch2\u003EConfigure linked & staging linked services\u003C/h2\u003E\n","\u003Cp\u003EThe following sections give the main steps to configure ADF. Otherwise, use the provided ADF ARM template to deploy.\u003C/p\u003E\n","\u003Ch3\u003ECreate linked service to SAP\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EFrom Azure Data Factory, select \u003Cstrong\u003EManage\u003C/strong\u003E > Linked services > Create linked service.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESearch for SAP CDC and select Continue.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EEnter the following details:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EName: \u003Ccode\u003EABA_ODP\u003C/code\u003E, or the name of your SAP system.\u003C/li\u003E\u003Cli\u003EIntegration runtime: \u003Ccode\u003ESapIR\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EIP address of the SAP system.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E <aside class="callout">\nYou can get the ip address from Azure Home > Virtual Machines > Linux machine, or from SAP CAL.\n</aside>\n* System number: `00`\n* Client ID: `100`\n* Language: `en`\n* SNC mode: **Off**\n* User name: `idadmin`\n* Password: `ides123` (or check the Getting Started Guide for the SAP instance)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETest connection\u003C/strong\u003E. If it fails, check that you installed \u003Ccode\u003ENco 3.0\u003C/code\u003E on the Windows virtural machine, and configured the in-bound rules ports 3200 or 3300 in Azure.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate staging linked service to storage\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EFrom Azure Data Factory Designer, select \u003Cstrong\u003EManage\u003C/strong\u003E > Linked services > Create linked service.\u003C/li\u003E\u003Cli\u003ESearch for Azure and select \u003Cstrong\u003EAzure Data Lake Storage Gen2\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESelect Continue.\u003C/li\u003E\u003Cli\u003EName: \u003Ccode\u003Eazurestage\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003ESelect from Azure subscription.\u003C/li\u003E\u003Cli\u003ESelect the Storage account name, \u003Ccode\u003Eazurestage\u003C/code\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate linked service to Snowflake\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EFrom Azure Data Factory Designer, select \u003Cstrong\u003EManage\u003C/strong\u003E > Linked services > Create linked service.\u003C/li\u003E\u003Cli\u003ESearch for Snowflake and select \u003Cstrong\u003EContinue\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EConnect via integration runtime, \u003Cstrong\u003EAutoResolveIntegrationRuntime\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EFill in the connection information to your Snowflake account.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch2\u003ECreate source & sink datasets\u003C/h2\u003E\n","\u003Ch3\u003ECreate fi_ar_4 source datset\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EFrom Azure Data Factory Designer, select \u003Cstrong\u003EAuthor\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect Datasets and click on  \u003Cstrong\u003E(...)\u003C/strong\u003E > New dataset\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESearch SAP CDC, Select and Continue.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EEnter the following:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EName: \u003Ccode\u003Esapfi_ar_4\u003C/code\u003E\u003C/li\u003E\u003Cli\u003ELinked Service: \u003Ccode\u003EABA_ODP\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EIntegration runtime: \u003Ccode\u003ESapIR\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EODP Context: \u003Cstrong\u003ESAPI\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EODP Name: \u003Cstrong\u003E0FI_AR_4\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThe dataset is created.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect Preview data. The data appears:\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/adf_preview_ar_4.png\" alt=\"ADF Preview AF4\"\u003E\u003C/p\u003E\n","\u003Cp\u003EIf the preview does not work, you may have to turn on the debugging.\u003C/p\u003E\n","\u003Ch3\u003ECreate new data sources in SAP\u003C/h3\u003E\n","\u003Cp\u003ESome tables may not be exposed to ODP in your trial system. Not to worry, you can use transaction \u003Cstrong\u003ERSO2\u003C/strong\u003E and create new data sources.\u003C/p\u003E\n","\u003Ch4\u003EExpose customer & currency tables to ODP in SAP\u003C/h4\u003E\n\u003Col\u003E\u003Cli\u003EFrom SAP GUI, enter transaction /nRSO2 (that's the letter O, not zero (0)).\n\u003Col\u003E\u003Cli\u003ECreate a new datasource\n\u003Cul\u003E\u003Cli\u003ESelect Master Data Attributes\u003C/li\u003E\u003Cli\u003EEnter name for new data source, \u003Ccode\u003EZTCURR\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003ESelect Create.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/RSO2_create_datasource.png\" alt=\"RS02 Create Datasource\"\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EA configuration window opens. Click on the loop next to \u003Cstrong\u003EApplic. Component\u003C/strong\u003E.\n\u003Col\u003E\u003Cli\u003ESelect SAP-R/3 > 0CS > 0CS-IO (or your choice of component).\u003C/li\u003E\u003Cli\u003EDouble-click on \u003Cstrong\u003EOCS-IO\u003C/strong\u003E. You return to the previous screen.\u003C/li\u003E\u003Cli\u003EEnter Currency for the short, medium, and long description.\u003C/li\u003E\u003Cli\u003EEnter \u003Ccode\u003ETCURR\u003C/code\u003E in the View/Table.\u003C/li\u003E\u003Cli\u003EClick the diskette icon (save).\n\u003Col\u003E\u003Cli\u003ESelect Local Object. You may have to do this twice. The fields for TCURR appear.\u003C/li\u003E\u003C/ol\u003E\n\u003C/li\u003E\u003Cli\u003ERepeat the above steps for Customer, naming the table \u003Ccode\u003EZCUSTOMER_ATTR\u003C/code\u003E and pointing to the table \u003Ccode\u003EKNA1\u003C/code\u003E.\u003C/li\u003E\u003C/ol\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch4\u003ECreate remaining source datasets\u003C/h4\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EFrom Azure Data Factory, select \u003Cstrong\u003EAuthor\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect Datasets and click on  \u003Cstrong\u003E(...)\u003C/strong\u003E > New dataset\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESearch SAP CDC, Select and Continue\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EName: \u003Ccode\u003ECurrency\u003C/code\u003E\u003C/li\u003E\u003Cli\u003ELinked Service: \u003Ccode\u003EABA_ODP\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EIntegration runtime: \u003Ccode\u003ESapIR\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EODP Context: \u003Cstrong\u003ESAPI\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EODP Name: \u003Cstrong\u003EZTCURR\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThe dataset is created.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect Preview data. The data appears.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ERepeat the above for the customer data source.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate sink datasets\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EFrom Azure Data Factory, select \u003Cstrong\u003EAuthor\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESelect Datasets and click on \u003Cstrong\u003E(...)\u003C/strong\u003E > New dataset\u003C/li\u003E\u003Cli\u003ESearch Snowflake, Select and Continue\u003C/li\u003E\u003Cli\u003EFor table name, select edit. For Schema put \u003Ccode\u003Esap_raw\u003C/code\u003E, for the name put \u003Ccode\u003Eztcurr_attr\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003ERepeat the above steps for the sinks \u003Ccode\u003E0customer_attr\u003C/code\u003E and \u003Ccode\u003E0fi_ar_4\u003C/code\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch2\u003ECreate data flows\u003C/h2\u003E\n","\u003Cp\u003E<aside class="callout">\nThese steps are only shown as an example, and following along with the example may require additional rights in third-party data, products, or services that are not owned or provided by Snowflake.  Please ensure that you have the appropriate rights in third-party data, products, or services before continuing.\n</aside>\n### Create df_FIAR4_trunc_full_load\n1. From Azure Data Factory, select **Author** \n1. Select Dataflows and click on **(...)** > New dataflow. \n1. Name the dataflow df_FIAR4_trunc_full_load.\n1. Select the box in the flow.\n1. In Source settings tab:\n1.  name the Output stream name sapFiar4.\n1. Add the description: Import data from sapFiar4.\n1. Choose Dataset as the Source type.\n1. Choose sapFiar4 as the dataset. Toggle **Data flow debug** to test the connection.\n1. Select the options: Allow sehema drift, Infer drifted column types, and Validate schema\n1. Select Currency as a source\n1. Select the **+ button**, scroll to the bottom and choose **sink**.\n1. In the Source options tab, choose **Full on every run** for the Run mode.\n1. In the Projection tab, check the column names and type. \n1. Leave the defaults for the other tabs.\n1. Click the + sign found to the lower right of the output stream, and choose **Sink**.\n1. In the Sink tab:\n1. Name the Output stream name of the sink to snowFiar4.\n1. Add a description.\n1. Choose the 0fi_ar_4 dataset\n1. Select the optoins, Allow schema drift and Validate schema.\n1. In the Settings tab:\n1. Select Allow insert\n1. Select the toggle Recreate Table.\n1. In the Mapping tab:\n1.  Choose the options to Skip duplicate input columns and Skip duplicate output columns.\n1. Choose Auto mapping.\u003C/p\u003E\n","\u003Ch3\u003ECreate df_MASTER_trunc_full_load\u003C/h3\u003E\n","\u003Cp\u003EFollow the steps above, but create flows for sapCurrency -> ztcurr_attr, and sapCustomer -> 0custoemr_attr\u003C/p\u003E\n","\u003Ch3\u003ECreate df_FIAR4_delta_load\u003C/h3\u003E\n","\u003Cp\u003EFollow the steps above, but choose Incremental changes only in the source options for sapFiar4 as the datasource and 0fi_ar_4 as the sink.\u003C/p\u003E\n","\u003Cp\u003EIn the sink, make sure that all the options are selected and the key columns are mapped.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/df_delta.png\" alt=\"DF Delta\"\u003E\u003C/p\u003E\n","\u003Ch2\u003ECreate & trigger pipeline\u003C/h2\u003E\n","\u003Cp\u003EUsing a combination of the data flows, build pipelines. Here is an example of a full load pipeline:\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/pipeline_full.png\" alt=\"Pipeline Full\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENotice, in Settings, the Compute Size (Small),  the staging linked service (azurestage) and the Staging storage folder (sap_/ar).\u003C/p\u003E\n","\u003Cp\u003ETo trigger the pipeline:\nFrom Data Factory > Author > Pipelines > pipe_all_recreate_full_load, select Add trigger > Trigger Now > OK.\u003C/p\u003E\n","\u003Cp\u003EMonitor the pipeline run. (My run, with a Small compute on the ADF side, took about five minutes.)\u003C/p\u003E\n","\u003Cp\u003EIn Snowflake, you can also monitor the progress through Query History\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/sf_full_load.png\" alt=\"SF Full Load\"\u003E\u003C/p\u003E\n","\u003Ch2\u003EClone project, install dbt, python & packages\u003C/h2\u003E\n","\u003Ch3\u003EClone the dbt project from git\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EOpen a terminal on your local machine.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EMake and navigate to the directory where you want the dbt project to reside, for example in your home directory:\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sh\"\u003E$ cd ~/\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col\u003E\u003Cli\u003EWithin the above directory, run the following command to clone the project from github:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sh\"\u003E$ git clone https://github.com/Snowflake-Labs/sf-samples.git                       \n\u003C/code\u003E\u003C/pre\u003E\n\u003Col\u003E\u003Cli\u003ECheck that the project (a set of directories and files) has been downloaded:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sh\"\u003E $ ls sf-samples/samples/sap_accounts_receivable_dbt\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou should see the following directories and files:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sh\"\u003EDockerfile\t\tdocumentation\t\tprofiles.example.yml\nREADME.md\t\tgenerators\t\trequirements.txt\nanalysis\t\tmacros\t\t\tsnapshots\ndata\t\t\tmodels\t\t\ttableau\ndbt_project.yml\t\tpackages.yml\t\ttests\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EInstall dbt & python\u003C/h3\u003E\n","\u003Cp\u003EIf you already have dbt installed, feel free to skip this step.\u003C/p\u003E\n","\u003Cp\u003EInstall \u003Ca href=\"https://www.getdbt.com/\"\u003Edbt\u003C/a\u003E using the following command that sources the right requirements.\nUse the \u003Ccode\u003Erequirements.txt\u003C/code\u003E in the project directory which includes the most recent tested version of Snowflake compatible package.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sh\"\u003E$ cd ~/sf-samples/samples/sap_accounts_receivable_dbt\n$ pip3 install -r requirements.txt --upgrade\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EVerify that dbt was installed:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sh\"\u003E$ dbt --version\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou will get a message similiar to the following (version might vary):\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sh\"\u003Einstalled version: 1.0.1\n   latest version: 1.0.1\n\nUp to date!\n\nPlugins:\n  - snowflake: 1.0.0\n\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E<aside class="negative">\nIf you face any issues please refer to the official installation guide for dbt core.\n</aside>\u003C/p\u003E\n","\u003Ch3\u003EInstall additional dbt packages\u003C/h3\u003E\n","\u003Cp\u003EOur project uses third-party modules. Install them using this command in the repository folder:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E$ dbt deps\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis creates a new folder \u003Ccode\u003Edbt_packages\u003C/code\u003E directory in your project.\u003C/p\u003E\n","\u003Cp\u003EOk! let's get to configuring the project in the next section!\u003C/p\u003E\n","\u003Ch2\u003EPoint dbt project to Snowflake\u003C/h2\u003E\n\u003Col\u003E\u003Cli\u003ETo point dbt to your Snowflake instance, open file \u003Ccode\u003E~/.dbt/profiles.yml\u003C/code\u003E in your prefered text editor\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003EOpen  ~/.dbt/profiles.yml\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003ECopy the text below and paste it into  profiles.yml:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-yaml\"\u003Esap_dbt_lab:\n  target: default\n  outputs:\n    default:\n      type: snowflake\n      account: <mysnowflakeacccount>\n      \n      user: sap_dbt_user\n      password: <mysecretpassword>\n      # If you want run an account with SSO uncomment following line and remove the password line\n      # authenticator: externalbrowser\n      \n      role: sap_dbt_role\n      warehouse: sap_dbt_wh\n      database: sap_demo # Database must exist prior to running \n      schema: sap_raw\n      threads: 8\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EEdit <mysnowflakeacccount> and replace it with your Snowflake account name (for example eu_demo123.eu-central-1, without the https:// and without .snowflakecomputing.com).\u003C/li\u003E\u003Cli\u003EEdit <mysecretpassword> and replace it with the password you set for sap_dbt_user.\u003C/li\u003E\u003Cli\u003ESave the file.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003ETo learn more about the profiles.yml, see \u003Ca href=\"https://docs.getdbt.com/dbt-cli/configure-your-profile\"\u003Ehere\u003C/a\u003E.\u003C/p\u003E\n","\u003Cp\u003EUse this command to check the connection details, dependencies, and that all required databases exist:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E$ dbt compile\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFix any errors thrown by this command.\u003C/p\u003E\n","\u003Cp\u003EOK! Now we are ready to run our data flow in the next section!\u003C/p\u003E\n","\u003Ch2\u003ERun dbt model\u003C/h2\u003E\n","\u003Cp\u003E\u003Ccode\u003Edbt run\u003C/code\u003E executes compiled sql model files, in this case pulling data from the SAP_RAW schema and transforming it at various stages until we reach the datamart schema. Models are run in the order defined by the dependency graph generated during compilation. Intelligent multi-threading is used to minimize execution time without violating dependencies.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E$ dbt run\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EResults look like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E13:48:47  2 of 13 START view model sap_l10_staging.ods_0fi_ar_4........................... [RUN]\n13:48:47  3 of 13 START view model sap_l10_staging.ods_2lis_12_vcitm...................... [RUN]\n13:48:47  4 of 13 START view model sap_l10_staging.ods_ztcurr_attr........................ [RUN]\n13:48:47  1 of 13 START view model sap_l10_staging.ods_0customer_attr..................... [RUN]\n13:48:50  4 of 13 OK created view model sap_l10_staging.ods_ztcurr_attr................... [SUCCESS 1 in 2.84s]\n13:48:50  5 of 13 START view model sap_l15_semantic.en_ztcurr_attr........................ [RUN]\n13:48:50  2 of 13 OK created view model sap_l10_staging.ods_0fi_ar_4...................... [SUCCESS 1 in 2.87s]\n13:48:50  6 of 13 START view model sap_l15_semantic.en_0fi_ar_4........................... [RUN]\n13:48:50  1 of 13 OK created view model sap_l10_staging.ods_0customer_attr................ [SUCCESS 1 in 2.87s]\n13:48:50  7 of 13 START view model sap_l15_semantic.en_0customer_attr..................... [RUN]\n13:48:50  3 of 13 OK created view model sap_l10_staging.ods_2lis_12_vcitm................. [SUCCESS 1 in 2.92s]\n13:48:50  8 of 13 START view model sap_l15_semantic.en_2lis_12_vcitm...................... [RUN]\n13:48:53  6 of 13 OK created view model sap_l15_semantic.en_0fi_ar_4...................... [SUCCESS 1 in 3.11s]\n13:48:53  5 of 13 OK created view model sap_l15_semantic.en_ztcurr_attr................... [SUCCESS 1 in 3.15s]\n13:48:53  9 of 13 START view model sap_l15_semantic.currency.............................. [RUN]\n13:48:53  8 of 13 OK created view model sap_l15_semantic.en_2lis_12_vcitm................. [SUCCESS 1 in 3.07s]\n13:48:53  7 of 13 OK created view model sap_l15_semantic.en_0customer_attr................ [SUCCESS 1 in 3.13s]\n13:48:53  10 of 13 START view model sap_l20_transform.delivery_item_data.................. [RUN]\n13:48:56  9 of 13 OK created view model sap_l15_semantic.currency......................... [SUCCESS 1 in 2.20s]\n13:48:56  11 of 13 START view model sap_l15_semantic.currency_0fi_ar_4.................... [RUN]\n13:48:56  10 of 13 OK created view model sap_l20_transform.delivery_item_data............. [SUCCESS 1 in 2.56s]\n13:48:58  11 of 13 OK created view model sap_l15_semantic.currency_0fi_ar_4............... [SUCCESS 1 in 2.50s]\n13:48:58  12 of 13 START view model sap_l20_transform.accounts_receivable................. [RUN]\n13:49:00  12 of 13 OK created view model sap_l20_transform.accounts_receivable............ [SUCCESS 1 in 2.26s]\n13:49:00  13 of 13 START table model sap_l30_mart.accounts_receivable_mart................ [RUN]\n13:49:11  13 of 13 OK created table model sap_l30_mart.accounts_receivable_mart........... [SUCCESS 1 in 10.46s]\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAfter the run your Snowflake Account should look like:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/snowflake_target_state.png\" alt=\"Snowflake Target State\"\u003E\u003C/p\u003E\n","\u003Ch2\u003EVisualize your data flow!\u003C/h2\u003E\n","\u003Cp\u003Edbt automatically generates the model code, a DAG of your project, any tests you've added to a column, and enables you to annotate models, columns, and sources! This is critically important for lineage, impact analysis, troubleshooting, and just plain visibility into your project!\u003C/p\u003E\n","\u003Cp\u003ETo generate and serve your data flow:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EFrom the terminal\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E$ dbt docs generate\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003EOnce the docs are generated, you will want to view them in the browser, so run this command:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003E$ dbt docs serve\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis command can be rerun for every model and documentation change.\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003E\n","\u003Cp\u003EThe browser window opens automatically. Otherwise navigate to \u003Ca href=\"http://localhost:8080\"\u003Ehttp://localhost:8080\u003C/a\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/dbt_doc1.png\" alt=\"Data Share\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect the data flow button in the bottom right to see the data flow:\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/dbt_ar.png\" alt=\"Tableau Dashboard\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EYou can access the lineage graph at any time using the graph button in the bottom right corner.\nFor more information see \u003Ca href=\"https://docs.getdbt.com/docs/building-a-dbt-project/documentation\"\u003Ehere\u003C/a\u003E\u003C/p\u003E\n","\u003Ch2\u003ETrack your DSO in Tableau\u003C/h2\u003E\n","\u003Cp\u003EVisualize your Days of Sales Outstanding (DSO) by geography and customer through this Tableau dashboard!\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/Account_Receivable_Dasboard_Tableau.png\" alt=\"Tableau Dashboard\"\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ELaunch Tableau Desktop.\u003C/li\u003E\u003Cli\u003ENavigate to \u003Ccode\u003E~/sf-samples/samples/sap_accounts_receivable_dbt/tableau\u003C/code\u003E and open \u003Ccode\u003EAccount_Receivables.twbx_v1\u003C/code\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EAlternatively you can launch from a command line:\n/Applications/Tableau\\ Desktop\\ 2021.3.app/Contents/MacOS/Tableau -f ~/sf-samples/samples/sap_accounts_receivable_dbt/tableau/Account_Receivables_v1.twbx\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EYou are prompted for the password. Wait! You need to edit the connection first!\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Ccode\u003EEdit connection\u003C/code\u003E  and adjust the connection settings to your instance:\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/edit_tableau_connection.png\" alt=\"Edit Tableau Connection\"\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Ccode\u003ESign In\u003C/code\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EOnce the connection is established you will be redirected to the main Dashboard visualizing the resulting data mart\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch3\u003EOptional: Create Snowsight dashboard\u003C/h3\u003E\n","\u003Cp\u003EYou can find some example queries in the analysis director of the project, for example for dso details analysis\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT \n  COMPANY_CODE\n  , DOCUMENT_TYPE\n  , DOCUMENT_NUMBER\n  , POSTING_DATE\n  , CLEARING_DATE\n  , DEBIT_AMT_LOCAL_CURRENCY\n  , STATUS\n  , DSO \nFROM {{ ref('accounts_receivable_mart') }} \nWHERE DOCUMENT_TYPE='RV'\nORDER BY DEBIT_AMT_LOCAL_CURRENCY DESC;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch2\u003EConclusion\u003C/h2\u003E\n","\u003Cp\u003EGreat job! This demo gives an example environment of how to transform SAP accounts receivable into a data mart.\u003C/p\u003E\n","\u003Cp\u003EDuring this tutorial you learned following topics:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EConfiguring your Snowflake account\u003C/li\u003E\u003Cli\u003EInstallation and configuration of dbt\u003C/li\u003E\u003Cli\u003EWorking with the dbt documentation\u003C/li\u003E\u003Cli\u003EConnecting a Tableau Dashboard\u003C/li\u003E\u003Cli\u003EDemonstrating SAP Accounts Receivable data\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EOptional: Clean up environment\u003C/h3\u003E\n","\u003Ch4\u003EClean up Snowflake\u003C/h4\u003E\n","\u003Cp\u003EUse the following commands in a Snowflake worksheet to permanently delete databases, warehouse, role and user.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE accountadmin;\nDROP DATABASE IF EXISTS sap_demo;\nDROP WAREHOUSE IF EXISTS sap_dbt_wh;\nDROP ROLE IF EXISTS sap_dbt_role;\nDROP USER IF EXISTS sap_dbt_user;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch4\u003EClean up Local machine\u003C/h4\u003E\n\u003Col\u003E\u003Cli\u003EUse pip uninstall to remove the dbt and packages. Run this before deleting the \u003Ccode\u003Esf-samples\u003C/code\u003E directory if you want to delete the snowflake adapter and other directories, which are located under ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt/.\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-Bash\"\u003E$ cd ~/sf-samples/samples/sap_accounts_receivable_dbt\n$ pip3 uninstall -r requirements.txt\n\nFound existing installation: dbt-snowflake 1.0.0\nUninstalling dbt-snowflake-1.0.0:\n  Would remove:\n    ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt/adapters/snowflake/*\n    ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt/include/snowflake/*\n    ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt_snowflake-1.0.0.dist-info/*\nProceed (Y/n)? Y\nSuccessfully uninstalled dbt-snowflake-1.0.0\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003ERemoving the sf-samples repo. To remove the demo package you can simply delete the directory \u003Ccode\u003E~/sf-samples/samples/sap_accounts_receivable_dbt\u003C/code\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EOptional: SAP extractors\u003C/h3\u003E\n","\u003Cp\u003EThere are \u003Ca href=\"https://medium.com/snowflake/if-extraction-from-sap-were-easy-b5f3d02f0ec9\"\u003Eseveral tools on the market\u003C/a\u003E to manage initial and delta extractions from SAP. This section simply gives a couple of example applications that extract data from SAP.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EIt is not required to perform the steps in the videos.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EWatch "How to \u003Ca href=\"https://www.youtube.com/watch?v=EwhgASMXGR4\"\u003Einstall Qlik Replicate\u003C/a\u003E" video to get data out of an SAP system\u003C/p\u003E\n","\u003Cp\u003EWatch "\u003Ca href=\"https://www.youtube.com/watch?v=PyybzHl6A3M\"\u003EHow to use SNP Glue\u003C/a\u003E " video to get data out of an SAP systems\u003C/p\u003E\n","\u003Ch3\u003EAppendix: Business Semantics\u003C/h3\u003E\n","\u003Cp\u003EAll downstream descriptions and translation of the SAP columns are auto-generated. We used publicly available column information and consolidated them into a single machine-parsable csv file to generate the documentation. The used code can be found in the dbt project under the \u003Ccode\u003E/generators\u003C/code\u003E folder.\u003C/p\u003E\n","\u003Cp\u003ETo regenerate or extend the source documentation it is suggested to update the raw data and use the \u003Ccode\u003Egenerate_dbt_source.py\u003C/code\u003E script. That script will lookup all available source tables and columns and add corresponding fields to the dbt documentation.\u003C/p\u003E\n","\u003Cp\u003EFor further details on the available scripts please refer to the \u003Ccode\u003EREADME.md\u003C/code\u003E in the generators folder or see the commented source code.\u003C/p\u003E\n","\u003Ch3\u003EFurther reading\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://resources.snowflake.com/migration-guides/migrating-from-sap-to-snowflake\"\u003ESAP to Snowflake transformations\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://medium.com/snowflake/if-extraction-from-sap-were-easy-b5f3d02f0ec9\"\u003EConnecting to SAP\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"/en/developers/guides/data-teams-with-dbt-core/\"\u003EAccelerating Data Teams with dbt Core & Snowflake\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://medium.com/@sasha.mitrovich/optimize-your-hierarchical-data-with-snowflake-part-one-508384b9b857\"\u003EOptimising hierarchical data in Snowflake\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://medium.com/snowflake/curry-encies-never-tasted-so-good-36dcecfcd0bd\"\u003ESAP currency conversion in Snowflake\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://blog.getdbt.com/how-we-configure-snowflake/\"\u003EHow we (DBT) configure Snowflake by Fishtown Team\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://about.gitlab.com/handbook/business-technology/data-team/platform/dbt-guide/#model-structure\"\u003EModel Structure by GitLab team\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"SAP Accounts Receivable to Snowflake using ADF",":items":{},":itemsOrder":[],":type":"snowflake-site/components/contentfragment","elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"## Overview \n\nThis step-by-step shows you how to:\n* Deploy an SAP ECC demo system in Azure using SAP CAL:\n\n![cal](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/cal.png)\n\n* Activate your Snowflake account:\n\n\n![Snowflake Account](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/snow.png)\n\n\n* Extract and load Accounts Receivable data through 0fi_ar_4 extractor--\u003EODP API --\u003EAzure Data Factory to Snowflake, full and delta:\n\n![Data flow](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/df_overview.png)\n\n\n* Use pre-built [dbt CLI](https://docs.getdbt.com/dbt-cli/cli-overview) data flows to:\n  * translate technical field names into business friendly terms\n  * perform a currency conversion transform\n  * combine customer master data with accounts documents.\n\nThis is a screen capture of DBT's auto-documentation of the data flow we will create:\n\n![DBT Data Flow](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/dbt_ar.png)\n\nWe provide a Tableau report to visualize the data regionally, per customer, per DSO, and per document number. \n![Tableau Dashboard](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/Account_Receivable_Dasboard_Tableau.png)\nLet’s get started!\n\n### What you need to have before starting the lab\n\nTo participate in the virtual hands-on lab, attendees need the following:\n\n* Admin rights to an Azure trial account\n* [An SAP s- or p-user or linked Universal ID](https://blogs.sap.com/2020/01/17/creating-a-p-user-in-sap-cloud-platform-to-practise-sap-hana./) to log on to SAP's Cloud Appliance Library (cal.sap.com). \n* A credit card to add billing information to the Azure account \n* A Snowflake account with `ACCOUNTADMIN` access (you can get a [free Trial account here](https://signup.snowflake.com/?utm_cta=quickstarts_))\n* Familiarity with Snowflake and Snowflake objects (eg. through the [Zero-To-Snowflake hands-on-lab](/en/developers/guides/getting-started-with-snowflake/))\n* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) installed on your local machine\n* [Tableau desktop](https://www.tableau.com/products/desktop/download) installed on your local machine (optional)\n\n### What you will install during the lab\nYou will install [dbt CLI](https://docs.getdbt.com/dbt-cli/install/pip) during the lab.\n\nThe following will be installed or used in your Azure environment:\n* SAP ECC\n* a Windows virtual machine\n* an Azure self-hosted integrated runtime on the virtual machine\n* Azure Data Factory\n* an Azure auto resolve integration runtime.\n* ADLS Gen 2 storage\n\nYou will activate your Snowflake account.\n\n### What you will learn\n\n* How to deploye and activate an SAP test machine using SAP Computer Appliance Library.\n* How to use Azure Data Factory to request data from SAP through the ODP API.\n* How to install and run a pipelines using DBT & Snowflake.\n* How to transform SAP data in Snowflake.\n\n### What you will build\nAn Accounts Receivable pipeline for Financial Services from SAP ECC to Snowflake to Tableau.\n\n\n\u003C!-- ------------------------ --\u003E\n\n## Create Azure account & deploy SAP ERP\n\u003Caside class=\"callout\"\u003E\nIn the interest of getting data out of SAP for this lab, we will use Azure Data Factory's SAP CDC connector, but there are many other ways to do this, and we are not recommending this particular path. If you otherwise have access to the demo data in this lab, you can skip building the Azure and SAP environments and go directly to the sections of creating your Snowflake account and installing and configuring DBT.\n\u003C/aside\u003E\n\nIn this section, we:\ncreate and activate an Azure free-trial environment\naccess SAP Cloud Application Library (SAP CAL), choose a template and deploy:\n* SAP ERP 6.0 EHP6\n* Windows virtual machine\n* Subnets\n\n\u003Caside class=\"callout\"\u003E\nI use an SAP ECC instance, but you can adapt this quickstart to use an S/4HANA instance.\n\u003C/aside\u003E\n\nFor full documentation on the Azure/SAP setup, check [here](https://learn.microsoft.com/en-us/azure/data-factory/sap-change-data-capture-introduction-architecture).\n\nAlternatively, if you are on AWS, you can adapt from the following AWS lab: [SAP on AWS Beyond Lab](https://catalog.workshops.aws/sap-on-aws-beyond/en-US/01-preparation/60-sap-env).\n\n\n\u003Caside class=\"callout\"\u003E\nAfter this section you will set up the Snowflake account and Configure ADF. If you wish, you can configure Snowflake first.\n\u003C/aside\u003E\n\n### Use SAP CAL to create SAP ERP\nPrerequisites:\n  * Admin rights on an [Azure account](https://learn.microsoft.com/en-us/training/modules/create-an-azure-account/)\n  * Access to https://cal.sap.com\nUse the [this video](https://www.youtube.com/watch?v=iORePziUMBk) to set up your Azure account and create an SAP instance in Azure through SAP CAL:\n\n\nAdjust the following resources in Usage + quotas in your Azure subscription, before deploying from SAP CAL. \n  * Total Regional vCPUs to `50`.\n  * Standard ESv5 Family CPUs to `10` vCPU.\n  * Standard DSv5 Family CPUs to `10` vCPU.\n\n\u003Caside class=\"callout\"\u003E\nIDES trial accounts have data in them, but are limited to 30 days. Development accounts tend not to have data in them, but the developer licenses are renewable.\n\u003C/aside\u003E\n\nDeployment can easily take an **hour**, so now is a good time to go to the Snowflake section and follow the setup steps. When the instance is activated and Snowflake is configured, come back here and continue. \n### Test access to SAP\n1. From  cal.sap.com \u003E Appliances, select **Connect** next to your deployed appliance. \n1. Choose RDP \u003E Connect User name: Administrator, Password is the Master one you entered for the appliance.\n1. Double-click the **SAP Logon** icon.\n1. Click **Log On**:\n    * User: idadmin,\n    * Password: ides123 (or check the Getting Started Guide for the SAP instance)\n\n\u003Caside class=\"callout\"\u003E\nCheck that you have Accounting \u003E  Financial Accounting \u003E Accounts Receivable in the SAP menu. If you don't you may not have any data, and may have to terminate this instance and launch a new, different instance.\n\u003C/aside\u003E\n\n## Create & configure Snowflake\n1. Sign up for a Snowflake trial account at https://signup.snowflake.com/.\n1. Login to your Snowflake trial account.  \n![Login Screen](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/login_screen.png)\n\n1. Click [here](https://docs.snowflake.com/en/user-guide/snowflake-manager.html#quick-tour-of-the-web-interface) for a quick tour of the Snowflake's user interface, Snowsight.  \n \n\n3. Create a database and a service accounts for dbt. Create a worksheet, copy the below, paste into the worksheet,  change the password and run it.\n\n\u003Caside class=\"callout\"\u003E\nMake sure you change the password before running the script!\n\u003C/aside\u003E\n\n```sql\n-------------------------------------------\n-- create demo database\n-------------------------------------------\nUSE ROLE accountadmin;\nCREATE DATABASE IF NOT EXISTS sap_demo; \n-------------------------------------------\n-- create virtual warehouse compute cluster\n-------------------------------------------\nUSE ROLE sysadmin;\nCREATE OR REPLACE WAREHOUSE sap_dbt_wh \n  WAREHOUSE_SIZE = 'MEDIUM' \n  AUTO_SUSPEND = 60 \n  AUTO_RESUME = TRUE \n  MIN_CLUSTER_COUNT = 1 \n  MAX_CLUSTER_COUNT = 3 \n  INITIALLY_SUSPENDED = TRUE;\n-------------------------------------------\n-- role and user\n-------------------------------------------\nUSE ROLE securityadmin;\nCREATE OR REPLACE ROLE sap_dbt_role;\n------------------------------------------- Please replace with your dbt user password\nCREATE OR REPLACE USER sap_dbt_user default_role = sap_dbt_role default_warehouse = sap_dbt_wh PASSWORD = \"sap_dbt123!\";\n-------------------------------------------\n-- Grants\n-------------------------------------------\nGRANT ROLE sap_dbt_role TO USER  sap_dbt_user;\nGRANT ROLE sap_dbt_role TO ROLE sysadmin;\nGRANT ALL ON DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON ALL SCHEMAS IN DATABASE sap_demo  TO ROLE sap_dbt_role;\nGRANT ALL ON ALL TABLES IN DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON FUTURE SCHEMAS IN DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON FUTURE TABLES IN DATABASE sap_demo TO ROLE sap_dbt_role;\nGRANT ALL ON WAREHOUSE sap_dbt_wh TO ROLE sap_dbt_role;\n```\n\nAs result of these steps, you will have:\n*  one empty databases: `sap_demo`\n*  one virtual warehouse: `sap_dbt_wh`\n*  one role and one user: `sap_dbt_role` and `sap_dbt_user`\n\n\u003C!-- ------------------------ --\u003E\n\n\n\n## Create Azure Data Factory, runtimes & storage\nIn this section, we will set up:\n\n* Azure Data Factory \n* a self-hosted Integrated Run-time (IR) for the SAP to ADF connection\n* an Azure AutoResolveIR to connect to Snowflake \n* an ADLS Gen 2 storage area.\n\nFor more information on how to use Azure Data Factory, please see [here](https://learn.microsoft.com/en-us/azure/data-factory/). \n### Create Azure Data Factory\n1. From the remote desktop Windows machine that was deployed by CAL, access https://portal.azure.com/#home and select Data Factories\n1. Select **+ Create** and fill in the details.\n1. Select **West Europe** for the region.\n1. Review + create \u003E Read the Terms \u003E Create.\n1. The system creates the Data Factory. \n1. Select Go to resource \u003E Launch studio.\n\n### Create self-hosted integration runtime\n1. From Data Factory Studio select **Manage** from the left (Tool Box icon).\n1. Select Integration runtimes \u003E + New \u003E Azure, Self-Hosted \u003E Continue\n1. Select Self-Hosted \u003E Continue (yes, again...)\n1. Name it `SapIR`.\n1. Select **Create**.\n1. Select **Option 1: Express setup** to install the IR on the remote desktop Windows machine\n1. The executable downloads onto the remote machine. \n1. From the downloads, right-click on the executable, **run as Administrator**. The IR installs on the remote machine.\n1. Install the [SAP NCo 3.0](https://support.sap.com/en/product/connectors/msnet.html) (`not 3.1`), with option Install assemblies to GAC.\n1. Back in Home \u003E Virtual Machines \u003E ERP6... \u003E Networking, add inbound port rule for `3200` and `3300`. See [Setup SHIR](https://learn.microsoft.com/en-us/azure/data-factory/sap-change-data-capture-shir-preparation) for more detailed information. \n\n### Create ADLS Gen 2 storage\n1. From https://portal.azure.com/#home \u003E Storage, select + Create.\n1. Name it `azurestage`. \n1. Assign it to your subscription, sap resource group, and West Europe Region, with Standard performance, and Locally-redundant storage.\n1. Select Create. Azure deploys the storage.\n1. Go to Azure \u003E Storage \u003E `azurestage` \u003E Data Protection, and turn *off* **Enable soft delete for blobs**.\n\n\n## Configure linked & staging linked services\nThe following sections give the main steps to configure ADF. Otherwise, use the provided ADF ARM template to deploy.\n\n### Create linked service to SAP\n1. From Azure Data Factory, select **Manage** \u003E Linked services \u003E Create linked service.\n1. Search for SAP CDC and select Continue.\n1. Enter the following details:\n\n    * Name: `ABA_ODP`, or the name of your SAP system.\n    * Integration runtime: `SapIR`.\n    * IP address of the SAP system. \n    \u003Caside class=\"callout\"\u003E\n      You can get the ip address from Azure Home \u003E Virtual Machines \u003E Linux machine, or from SAP CAL.\n    \u003C/aside\u003E\n    * System number: `00`\n    * Client ID: `100`\n    * Language: `en`\n    * SNC mode: **Off**\n    * User name: `idadmin`\n    * Password: `ides123` (or check the Getting Started Guide for the SAP instance)\n1. Select **Create**.\n2. **Test connection**. If it fails, check that you installed `Nco 3.0` on the Windows virtural machine, and configured the in-bound rules ports 3200 or 3300 in Azure.\n\n### Create staging linked service to storage\n1. From Azure Data Factory Designer, select **Manage** \u003E Linked services \u003E Create linked service.\n1. Search for Azure and select **Azure Data Lake Storage Gen2**.\n1. Select Continue.\n1. Name: `azurestage`. \n1. Select from Azure subscription.\n1. Select the Storage account name, `azurestage`.\n\n### Create linked service to Snowflake\n1. From Azure Data Factory Designer, select **Manage** \u003E Linked services \u003E Create linked service.\n1. Search for Snowflake and select **Continue**.\n1. Connect via integration runtime, **AutoResolveIntegrationRuntime**.\n1. Fill in the connection information to your Snowflake account.\n\n## Create source & sink datasets\n### Create fi_ar_4 source datset\n1. From Azure Data Factory Designer, select **Author** \n2. Select Datasets and click on  **(...)** \u003E New dataset\n3. Search SAP CDC, Select and Continue.\n1. Enter the following:\n    * Name: `sapfi_ar_4`\n    * Linked Service: `ABA_ODP`\n    * Integration runtime: `SapIR`\n    * ODP Context: **SAPI**\n    * ODP Name: **0FI_AR_4**\n\n    The dataset is created.\n4. Select Preview data. The data appears:\n\n![ADF Preview AF4](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/adf_preview_ar_4.png)\n\n\nIf the preview does not work, you may have to turn on the debugging.\n\n### Create new data sources in SAP\nSome tables may not be exposed to ODP in your trial system. Not to worry, you can use transaction **RSO2** and create new data sources. \n#### Expose customer & currency tables to ODP in SAP\n\n1. From SAP GUI, enter transaction /nRSO2 (that's the letter O, not zero (0)).\n    1. Create a new datasource\n        * Select Master Data Attributes\n        * Enter name for new data source, `ZTCURR`.\n        * Select Create. \n\n![RS02 Create Datasource](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/RSO2_create_datasource.png)\n\n 1. A configuration window opens. Click on the loop next to **Applic. Component**.\n    1. Select SAP-R/3 \u003E 0CS \u003E 0CS-IO (or your choice of component). \n    2. Double-click on **OCS-IO**. You return to the previous screen.\n    1. Enter Currency for the short, medium, and long description.\n    1. Enter `TCURR` in the View/Table.\n    1. Click the diskette icon (save).\n        1. Select Local Object. You may have to do this twice. The fields for TCURR appear.\n    1. Repeat the above steps for Customer, naming the table `ZCUSTOMER_ATTR` and pointing to the table `KNA1`.\n\n#### Create remaining source datasets\n1. From Azure Data Factory, select **Author**.\n2. Select Datasets and click on  **(...)** \u003E New dataset\n3. Search SAP CDC, Select and Continue\n    * Name: `Currency`\n    * Linked Service: `ABA_ODP`\n    * Integration runtime: `SapIR`\n    * ODP Context: **SAPI**\n    * ODP Name: **ZTCURR**\n\n    The dataset is created.\n4. Select Preview data. The data appears.\n1. Repeat the above for the customer data source.\n\n### Create sink datasets\n1. From Azure Data Factory, select **Author**.\n2. Select Datasets and click on **(...)** \u003E New dataset\n1. Search Snowflake, Select and Continue\n1. For table name, select edit. For Schema put `sap_raw`, for the name put `ztcurr_attr`.\n1. Repeat the above steps for the sinks `0customer_attr` and `0fi_ar_4`.\n\n## Create data flows\n\u003Caside class=\"callout\"\u003E\nThese steps are only shown as an example, and following along with the example may require additional rights in third-party data, products, or services that are not owned or provided by Snowflake.  Please ensure that you have the appropriate rights in third-party data, products, or services before continuing.\n\u003C/aside\u003E\n### Create df_FIAR4_trunc_full_load\n1. From Azure Data Factory, select **Author** \n1. Select Dataflows and click on **(...)** \u003E New dataflow. \n1. Name the dataflow df_FIAR4_trunc_full_load.\n1. Select the box in the flow.\n1. In Source settings tab:\n   1.  name the Output stream name sapFiar4.\n   1. Add the description: Import data from sapFiar4.\n   1. Choose Dataset as the Source type.\n   1. Choose sapFiar4 as the dataset. Toggle **Data flow debug** to test the connection.\n   1. Select the options: Allow sehema drift, Infer drifted column types, and Validate schema\n   1. Select Currency as a source\n   1. Select the **+ button**, scroll to the bottom and choose **sink**.\n1. In the Source options tab, choose **Full on every run** for the Run mode.\n1. In the Projection tab, check the column names and type. \n1. Leave the defaults for the other tabs.\n1. Click the + sign found to the lower right of the output stream, and choose **Sink**.\n1. In the Sink tab:\n    1. Name the Output stream name of the sink to snowFiar4.\n    1. Add a description.\n    1. Choose the 0fi_ar_4 dataset\n    1. Select the optoins, Allow schema drift and Validate schema.\n1. In the Settings tab:\n    1. Select Allow insert\n    1. Select the toggle Recreate Table.\n1. In the Mapping tab:\n    1.  Choose the options to Skip duplicate input columns and Skip duplicate output columns.\n    1. Choose Auto mapping.\n\n### Create df_MASTER_trunc_full_load\nFollow the steps above, but create flows for sapCurrency -\u003E ztcurr_attr, and sapCustomer -\u003E 0custoemr_attr\n\n### Create df_FIAR4_delta_load\nFollow the steps above, but choose Incremental changes only in the source options for sapFiar4 as the datasource and 0fi_ar_4 as the sink. \n\nIn the sink, make sure that all the options are selected and the key columns are mapped. \n![DF Delta](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/df_delta.png)\n\n## Create & trigger pipeline \nUsing a combination of the data flows, build pipelines. Here is an example of a full load pipeline:\n![Pipeline Full](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/pipeline_full.png)\n\nNotice, in Settings, the Compute Size (Small),  the staging linked service (azurestage) and the Staging storage folder (sap_/ar).\n\nTo trigger the pipeline:\nFrom Data Factory \u003E Author \u003E Pipelines \u003E pipe_all_recreate_full_load, select Add trigger \u003E Trigger Now \u003E OK.\n\nMonitor the pipeline run. (My run, with a Small compute on the ADF side, took about five minutes.)\n\nIn Snowflake, you can also monitor the progress through Query History\n![SF Full Load](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/sf_full_load.png)\n\n## Clone project, install dbt, python & packages\n\n### Clone the dbt project from git\n\n1. Open a terminal on your local machine.\n\n2. Make and navigate to the directory where you want the dbt project to reside, for example in your home directory:\n\n```sh\n$ cd ~/\n```\n1. Within the above directory, run the following command to clone the project from github:\n```sh\n$ git clone https://github.com/Snowflake-Labs/sf-samples.git                       \n```\n\n1. Check that the project (a set of directories and files) has been downloaded:\n```sh\n $ ls sf-samples/samples/sap_accounts_receivable_dbt\n```\nYou should see the following directories and files:\n```sh\nDockerfile\t\tdocumentation\t\tprofiles.example.yml\nREADME.md\t\tgenerators\t\trequirements.txt\nanalysis\t\tmacros\t\t\tsnapshots\ndata\t\t\tmodels\t\t\ttableau\ndbt_project.yml\t\tpackages.yml\t\ttests\n```\n### Install dbt & python\n\nIf you already have dbt installed, feel free to skip this step.\n\nInstall [dbt](https://www.getdbt.com/) using the following command that sources the right requirements.\nUse the `requirements.txt` in the project directory which includes the most recent tested version of Snowflake compatible package.\n```sh\n$ cd ~/sf-samples/samples/sap_accounts_receivable_dbt\n$ pip3 install -r requirements.txt --upgrade\n```\nVerify that dbt was installed:\n```sh\n$ dbt --version\n```\n\nYou will get a message similiar to the following (version might vary):\n```sh\ninstalled version: 1.0.1\n   latest version: 1.0.1\n\nUp to date!\n\nPlugins:\n  - snowflake: 1.0.0\n\n```\n\u003Caside class=\"negative\"\u003E\nIf you face any issues please refer to the official installation guide for dbt core.\n\u003C/aside\u003E\n\n### Install additional dbt packages\nOur project uses third-party modules. Install them using this command in the repository folder:\n```bash\n$ dbt deps\n```\nThis creates a new folder `dbt_packages` directory in your project. \n\nOk! let's get to configuring the project in the next section!\n\n\n## Point dbt project to Snowflake\n\n1. To point dbt to your Snowflake instance, open file `~/.dbt/profiles.yml` in your prefered text editor \n\n```bash\nOpen  ~/.dbt/profiles.yml\n```\n2. Copy the text below and paste it into  profiles.yml:\n\n```yaml\nsap_dbt_lab:\n  target: default\n  outputs:\n    default:\n      type: snowflake\n      account: \u003Cmysnowflakeacccount\u003E\n      \n      user: sap_dbt_user\n      password: \u003Cmysecretpassword\u003E\n      # If you want run an account with SSO uncomment following line and remove the password line\n      # authenticator: externalbrowser\n      \n      role: sap_dbt_role\n      warehouse: sap_dbt_wh\n      database: sap_demo # Database must exist prior to running \n      schema: sap_raw\n      threads: 8\n```\n3. Edit \\\u003Cmysnowflakeacccount\\\u003E and replace it with your Snowflake account name (for example eu_demo123.eu-central-1, without the https:// and without .snowflakecomputing.com).\n4. Edit \\\u003Cmysecretpassword\\\u003E and replace it with the password you set for sap_dbt_user.\n5. Save the file.\n\nTo learn more about the profiles.yml, see [here](https://docs.getdbt.com/dbt-cli/configure-your-profile).\n\n\nUse this command to check the connection details, dependencies, and that all required databases exist:\n```bash\n$ dbt compile\n```\nFix any errors thrown by this command.\n\nOK! Now we are ready to run our data flow in the next section!\n\n## Run dbt model\n\n`dbt run` executes compiled sql model files, in this case pulling data from the SAP_RAW schema and transforming it at various stages until we reach the datamart schema. Models are run in the order defined by the dependency graph generated during compilation. Intelligent multi-threading is used to minimize execution time without violating dependencies.\n\n```bash\n$ dbt run\n```\n\nResults look like this: \n```bash\n13:48:47  2 of 13 START view model sap_l10_staging.ods_0fi_ar_4........................... [RUN]\n13:48:47  3 of 13 START view model sap_l10_staging.ods_2lis_12_vcitm...................... [RUN]\n13:48:47  4 of 13 START view model sap_l10_staging.ods_ztcurr_attr........................ [RUN]\n13:48:47  1 of 13 START view model sap_l10_staging.ods_0customer_attr..................... [RUN]\n13:48:50  4 of 13 OK created view model sap_l10_staging.ods_ztcurr_attr................... [SUCCESS 1 in 2.84s]\n13:48:50  5 of 13 START view model sap_l15_semantic.en_ztcurr_attr........................ [RUN]\n13:48:50  2 of 13 OK created view model sap_l10_staging.ods_0fi_ar_4...................... [SUCCESS 1 in 2.87s]\n13:48:50  6 of 13 START view model sap_l15_semantic.en_0fi_ar_4........................... [RUN]\n13:48:50  1 of 13 OK created view model sap_l10_staging.ods_0customer_attr................ [SUCCESS 1 in 2.87s]\n13:48:50  7 of 13 START view model sap_l15_semantic.en_0customer_attr..................... [RUN]\n13:48:50  3 of 13 OK created view model sap_l10_staging.ods_2lis_12_vcitm................. [SUCCESS 1 in 2.92s]\n13:48:50  8 of 13 START view model sap_l15_semantic.en_2lis_12_vcitm...................... [RUN]\n13:48:53  6 of 13 OK created view model sap_l15_semantic.en_0fi_ar_4...................... [SUCCESS 1 in 3.11s]\n13:48:53  5 of 13 OK created view model sap_l15_semantic.en_ztcurr_attr................... [SUCCESS 1 in 3.15s]\n13:48:53  9 of 13 START view model sap_l15_semantic.currency.............................. [RUN]\n13:48:53  8 of 13 OK created view model sap_l15_semantic.en_2lis_12_vcitm................. [SUCCESS 1 in 3.07s]\n13:48:53  7 of 13 OK created view model sap_l15_semantic.en_0customer_attr................ [SUCCESS 1 in 3.13s]\n13:48:53  10 of 13 START view model sap_l20_transform.delivery_item_data.................. [RUN]\n13:48:56  9 of 13 OK created view model sap_l15_semantic.currency......................... [SUCCESS 1 in 2.20s]\n13:48:56  11 of 13 START view model sap_l15_semantic.currency_0fi_ar_4.................... [RUN]\n13:48:56  10 of 13 OK created view model sap_l20_transform.delivery_item_data............. [SUCCESS 1 in 2.56s]\n13:48:58  11 of 13 OK created view model sap_l15_semantic.currency_0fi_ar_4............... [SUCCESS 1 in 2.50s]\n13:48:58  12 of 13 START view model sap_l20_transform.accounts_receivable................. [RUN]\n13:49:00  12 of 13 OK created view model sap_l20_transform.accounts_receivable............ [SUCCESS 1 in 2.26s]\n13:49:00  13 of 13 START table model sap_l30_mart.accounts_receivable_mart................ [RUN]\n13:49:11  13 of 13 OK created table model sap_l30_mart.accounts_receivable_mart........... [SUCCESS 1 in 10.46s]\n```\n\n\nAfter the run your Snowflake Account should look like:\n\n\n![Snowflake Target State](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/snowflake_target_state.png)\n\n\n\n## Visualize your data flow!\n\ndbt automatically generates the model code, a DAG of your project, any tests you've added to a column, and enables you to annotate models, columns, and sources! This is critically important for lineage, impact analysis, troubleshooting, and just plain visibility into your project! \n\nTo generate and serve your data flow:\n\n1. From the terminal\n```bash\n$ dbt docs generate\n```\n2. Once the docs are generated, you will want to view them in the browser, so run this command:\n\n```bash\n$ dbt docs serve\n```\nThis command can be rerun for every model and documentation change.\n\n3. The browser window opens automatically. Otherwise navigate to [http://localhost:8080](http://localhost:8080)\n![Data Share](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/dbt_doc1.png)\n\n4. Select the data flow button in the bottom right to see the data flow:\n![Tableau Dashboard](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/dbt_ar.png)\n\nYou can access the lineage graph at any time using the graph button in the bottom right corner.\nFor more information see [here](https://docs.getdbt.com/docs/building-a-dbt-project/documentation)\n## Track your DSO in Tableau\n\nVisualize your Days of Sales Outstanding (DSO) by geography and customer through this Tableau dashboard!\n![Tableau Dashboard](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/Account_Receivable_Dasboard_Tableau.png)\n\n\n1. Launch Tableau Desktop. \n2. Navigate to `~/sf-samples/samples/sap_accounts_receivable_dbt/tableau` and open `Account_Receivables.twbx_v1`\n\nAlternatively you can launch from a command line:\n/Applications/Tableau\\ Desktop\\ 2021.3.app/Contents/MacOS/Tableau -f ~/sf-samples/samples/sap_accounts_receivable_dbt/tableau/Account_Receivables_v1.twbx\n\n1. You are prompted for the password. Wait! You need to edit the connection first!\n\n2. Select `Edit connection`  and adjust the connection settings to your instance:\n![Edit Tableau Connection](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/sap-accounts-receivable-to-snowflake-using-adf/edit_tableau_connection.png)\n1. Select `Sign In`.\n\nOnce the connection is established you will be redirected to the main Dashboard visualizing the resulting data mart\n\n\u003C!-- ------------------------ --\u003E\n\n### Optional: Create Snowsight dashboard\n\nYou can find some example queries in the analysis director of the project, for example for dso details analysis\n\n```sql\nSELECT \n  COMPANY_CODE\n  , DOCUMENT_TYPE\n  , DOCUMENT_NUMBER\n  , POSTING_DATE\n  , CLEARING_DATE\n  , DEBIT_AMT_LOCAL_CURRENCY\n  , STATUS\n  , DSO \nFROM {{ ref('accounts_receivable_mart') }} \nWHERE DOCUMENT_TYPE='RV'\nORDER BY DEBIT_AMT_LOCAL_CURRENCY DESC;\n```\n\n## Conclusion\nGreat job! This demo gives an example environment of how to transform SAP accounts receivable into a data mart.  \n\nDuring this tutorial you learned following topics:\n* Configuring your Snowflake account\n* Installation and configuration of dbt\n* Working with the dbt documentation\n* Connecting a Tableau Dashboard\n* Demonstrating SAP Accounts Receivable data\n\n\n### Optional: Clean up environment\n\n#### Clean up Snowflake\nUse the following commands in a Snowflake worksheet to permanently delete databases, warehouse, role and user.\n\n```sql\nUSE ROLE accountadmin;\nDROP DATABASE IF EXISTS sap_demo;\nDROP WAREHOUSE IF EXISTS sap_dbt_wh;\nDROP ROLE IF EXISTS sap_dbt_role;\nDROP USER IF EXISTS sap_dbt_user;\n```\n\n#### Clean up Local machine\n1. Use pip uninstall to remove the dbt and packages. Run this before deleting the `sf-samples` directory if you want to delete the snowflake adapter and other directories, which are located under ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt/.\n\n```Bash\n$ cd ~/sf-samples/samples/sap_accounts_receivable_dbt\n$ pip3 uninstall -r requirements.txt\n\nFound existing installation: dbt-snowflake 1.0.0\nUninstalling dbt-snowflake-1.0.0:\n  Would remove:\n    ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt/adapters/snowflake/*\n    ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt/include/snowflake/*\n    ~/anaconda/anaconda3/lib/python3.9/site-packages/dbt_snowflake-1.0.0.dist-info/*\nProceed (Y/n)? Y\nSuccessfully uninstalled dbt-snowflake-1.0.0\n```\n2. Removing the sf-samples repo. To remove the demo package you can simply delete the directory `~/sf-samples/samples/sap_accounts_receivable_dbt`\n\n### Optional: SAP extractors\n\nThere are [several tools on the market](https://medium.com/snowflake/if-extraction-from-sap-were-easy-b5f3d02f0ec9) to manage initial and delta extractions from SAP. This section simply gives a couple of example applications that extract data from SAP. \n\n\u003E It is not required to perform the steps in the videos.\n\nWatch \"How to [install Qlik Replicate](https://www.youtube.com/watch?v=EwhgASMXGR4)\" video to get data out of an SAP system\n\nWatch \"[How to use SNP Glue](https://www.youtube.com/watch?v=PyybzHl6A3M) \" video to get data out of an SAP systems\n\n\n### Appendix: Business Semantics\n\nAll downstream descriptions and translation of the SAP columns are auto-generated. We used publicly available column information and consolidated them into a single machine-parsable csv file to generate the documentation. The used code can be found in the dbt project under the `/generators` folder.\n\nTo regenerate or extend the source documentation it is suggested to update the raw data and use the `generate_dbt_source.py` script. That script will lookup all available source tables and columns and add corresponding fields to the dbt documentation.\n\nFor further details on the available scripts please refer to the `README.md` in the generators folder or see the commented source code.\n\n### Further reading\n- [SAP to Snowflake transformations](https://resources.snowflake.com/migration-guides/migrating-from-sap-to-snowflake)\n- [Connecting to SAP](https://medium.com/snowflake/if-extraction-from-sap-were-easy-b5f3d02f0ec9)\n- [Accelerating Data Teams with dbt Core & Snowflake](/en/developers/guides/data-teams-with-dbt-core/)\n- [Optimising hierarchical data in Snowflake](https://medium.com/@sasha.mitrovich/optimize-your-hierarchical-data-with-snowflake-part-one-508384b9b857)\n- [SAP currency conversion in Snowflake](https://medium.com/snowflake/curry-encies-never-tasted-so-good-36dcecfcd0bd)\n- [How we (DBT) configure Snowflake by Fishtown Team](https://blog.getdbt.com/how-we-configure-snowflake/)\n- [Model Structure by GitLab team](https://about.gitlab.com/handbook/business-technology/data-team/platform/dbt-guide/#model-structure)\n","multiValue":false,":type":"text/x-markdown"},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image","multiValue":false,":type":"text/plain"}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"isDeveloperGuidesPage":false,"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-94bc1c98ca","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-e1ab3afca1",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-be66d55a0c","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2025-11-06",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-fd05636b76","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. 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Azure account & deploy SAP ERP\u003C/h2\u003E","\u003Ch2\u003ECreate & configure Snowflake\u003C/h2\u003E","\u003Ch2\u003ECreate Azure Data Factory, runtimes & storage\u003C/h2\u003E","\u003Ch2\u003EConfigure linked & staging linked services\u003C/h2\u003E","\u003Ch2\u003ECreate source & sink datasets\u003C/h2\u003E","\u003Ch2\u003ECreate data flows\u003C/h2\u003E","\u003Ch2\u003ECreate & trigger pipeline\u003C/h2\u003E","\u003Ch2\u003EClone project, install dbt, python & packages\u003C/h2\u003E","\u003Ch2\u003EPoint dbt project to Snowflake\u003C/h2\u003E","\u003Ch2\u003ERun dbt model\u003C/h2\u003E","\u003Ch2\u003EVisualize your data flow!\u003C/h2\u003E","\u003Ch2\u003ETrack your DSO in 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class=\"sf-footer__column-title\"\u003EProduct\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/platform/\"\u003EPlatform\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/product/snowflake-cowork/\"\u003ESnowflake CoWork\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/data-engineering/\"\u003EData Engineering\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/analytics/\"\u003EAnalytics\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/ai/\"\u003EAI\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/applications-and-collaboration/\"\u003EApplications & Collaboration\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca 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