--- sourceDocument: Australia Workflow Data Fabric sourceDocumentLink: https://www.servicenow.com/docs/r/australia/integrate-applications Release : - australia ft:locale : - en-US ft:publication_title : - Australia Workflow Data Fabric ft:clusterId : - crint bundleId : - crint workflow : - Creator --- # Extracting and transforming data # Extracting and transforming ERP data with Zero Copy Connector for ERP extraction tables {#ariaid-title1} Release version: Australia Updated October 22, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Extracting and transforming ERP data with Zero Copy Connector for ERP extraction tables Zero Copy Connector for ERP enables ServiceNow customers to efficiently extract large volumes of ERP data into local tables on the ServiceNow AI Platform. This process involves scheduling extraction jobs that pull data from ERP systems into temporary transform tables, where the data can be cleaned, processed, and mapped before being used in ERP models and applications. Show full answer Show less ## Key Features * **ERP Extraction Tables:** Serve as ETL data sources to regularly extract data, such as open purchase orders, from ERP systems into Glide tables on the AI Platform. * **Transform Tables and Table Maps:** Extracted data is first saved into temporary transform tables that act as intermediaries during data integration and transformation. You can create custom transform tables within the AI Platform's application scope to tailor data processing workflows. * **Configuration within AI Platform:** ETL processes for Zero Copy Connector are set up within the ServiceNow AI Platform app requiring the data, commonly via flows in Workflow Studio, rather than within the Zero Copy Connector app itself. * **Automatically Available Standard Extraction Tables:** Upon installing Zero Copy Connector for ERP, a predefined set of extraction tables covering sales, delivery, and procurement data are loaded automatically. Additional extraction tables from ERP Semantic Mining may also be available for existing instances. ## Key Outcomes * Enables scheduled, automated extraction of large ERP datasets into ServiceNow for real-time or batch processing. * Allows transformation and cleansing of ERP data before integration into ServiceNow applications, enhancing data accuracy and usability. * Supports creation of tailored data workflows and applications such as Source-to-Pay Operations and PO workspace via App Engine Studio. * Maintains compatibility as ERP Semantic Mining is phased out starting with the Zurich release, ensuring forward-looking data extraction strategies. Use ERP extraction tables in Zero Copy Connector for ERP to schedule processes that extract large volumes of ERP data into local tables on the ServiceNow AI Platform. Then the data is transformed with table maps and can be used in ERP models and applications. ## Data in extraction tables {#erp-canvas-extraction-tables__section_vwd_2s4_cyb} Use extraction tables, which are ETL (extract, transform, and load) data sources, to extract large amounts of data regularly. For example, you can extract all open purchase orders for the current month from an SAP system into a Glide table once a day at a set time. You can then access that data through ServiceNow AI Platform, such as Source-to-Pay Operations or a PO workspace created in App Engine Studio. After the extraction process is run, use import sets to map imported data into ServiceNow AI Platform tables. For more information, see [Import sets](https://www.servicenow.com/docs/1E08gh2tbmsMmPUp6Z9xQw "Import sets enable administrators to import data from various data sources, and then map that data into ServiceNow tables."). ## Extraction tables use transform table maps {#erp-canvas-extraction-tables__section_ubh_5ml_gyb} ERP extraction tables save data to a local transform table on the ServiceNow AI Platform. The transform table is a temporary table that holds data during the data integration or transformation process. Transform tables are an intermediary step before data is further processed, cleaned, or loaded into the target destination. For example, after import, the extraction table can run a Glide query on a transform table and save the output to several different target tables. If you use a custom transform table, you must first create the table on the ServiceNow AI Platform, and the table must be in the application scope. For more information on creating table transform maps, see [Create a transform map](https://www.servicenow.com/docs/gh_TgUejLqzUBNeH78dWWg "Every import operation to a production table requires at least one transform map associated with an import set."). ETL processes in Zero Copy Connector for ERP (Enterprise Resource Planning) are configured in the ServiceNow AI Platform app that needs the data, not Zero Copy Connector for ERP. For example, you can configure an extraction process in a flow in Workflow Studio. ## Automatically available standard extraction tables {#erp-canvas-extraction-tables__section_grc_hs4_cyb} When you install Zero Copy Connector for ERP, the ServiceNow AI Platform automatically loads a standard set of ERP extraction tables, including sales, delivery, and procurement tables. For a list of standard extraction tables, see [Standard extraction tables for Zero Copy Connector for ERP](https://www.servicenow.com/docs/gIUC6bo~7v28WadJ4rCdoQ "Zero Copy Connector for ERP provides standard extraction tables that you can link to enterprise resource planning (ERP) models."). If you installed ERP Semantic Mining, that app populates some additional extraction tables, such as ERP application activity, Collector directory data, and Namespace data. Important: Starting with the Zurich release, ERP Semantic Mining is being prepared for future deprecation. It will be hidden and no longer activated on new instances but will continue to be supported.