Import data from a file of any size into your Salesforce Org. The Data Flow guides you step by step through the importing process.

For now you can only insert data as new records into Salesforce, but in the future updating, exporting and other data processing options will be available for both Salesforce and Microsoft Dynamics. 

Prerequisites

• The file to import data from should:
  • Be a .csv or .xlsx file
  • Have a header row as the first row
  • For .xlsx files: Have a separate column for each field. Only the first sheet will be imported.
  • For .csv files: Use a back quote ( ` ), caret ( ^ ), comma ( , ), pipe ( | ), semicolon ( ; ) (Windows only), or tab as delimiter.
  • Have date format yyyy-mm-dd for date fields, and yyyy-MM-dd, yyyy-MM-ddTHH:mm:ss.SSSZ, or yyyy-MM-ddTHH:mm:ss.SSS+/-HH:mm for date/time fields.
• You have created a Connection to the Org or Environment you want to import your data into. 

Create a Data Flow for Import

Create a Plauti Cloud Data Flow for importing data into your Salesforce Org. 

You can pause setting up the Data Flow at any moment by closing the Data Flow window with the cross icon top right and then saving it. It will be saved on the “Drafts” tab for ten days; after that the draft will be deleted.

At each configuration step, click Next to proceed to the next step.

1. In Plauti Cloud, at left, go to Data Importer > Data Flows.
2. At top right, click + New Data Flow . 
   A pop-up window appears.
3. At File Type, select the source type of your data: CSV or Excel.
4. At Upload Source File, select your data file to import.
5. At Destination Type, select where you want to import to: e.g. “Salesforce”. 
6. At Select a Destination, select the Connection to the Org or Environment you want to import into. 
7. At Object or Entity, select the Object or Entity that the data is intended for.
8. At Configure Mapping, map the source field headers to fields on the Object or Entity. 
   • Where possible, source fields have already been mapped with a target field. This initial mapping is a suggestion; you can still pick another target field.
   • Fields marked with the Auto Mapping icon were mapped automatically based on earlier mappings. Read more on this below at Save Mappings for Future Use.
   • Select “Do not import this field” to skip a field. 
   • If a target field name is greyed out, or marked with a red line, it means you already selected it on another line. A target field can only be mapped once. 
   • A field marked in orange is not yet mapped. 
   • If a message is shown at the bottom, stating “You did not map all fields”, scroll up or down to find the unmapped fields, and map them or select “do not import”.
   • Some fields can be required to map. If you set such a field to "do not import", a message at the top will inform you that the field is required, and at the bottom you will see “You did not map all required fields” . Map it to a field instead.
   • At right, a source value is displayed as an example of what will be imported into the selected field. 
     Once you have mapped all fields you can continue.
9. At Overview, review the import settings. 
   If everything is correct, click Start to start the import.

You are redirected back to the Active & Finished Data Flows tab. Here you can follow the progress of the import.

Click Info or the name of the import to see the details of the import. Download logs with information about the succeeded and failed records in the Info window, or via the picklist next to the "Info” button.

Save Mappings for Future Use

The Auto Mapping feature remembers which source and target fields you mapped in earlier imports. 

Enable or disable Auto Mapping

1. At left, go to Data Importer > Settings.
2. At Auto Mapping, indicate per Connection whether you want to automatically enter mappings based on previous mapping choices. These automatic mappings can still be edited in the Data Flow configuration.
3. When mapping fields in a Data Flow, fields marked with the “Auto Mapping” icon were automatically mapped based on your earlier mappings. 

Remove saved mapping data

• To remove the saved mapping for a single field mapping: 
  1. When configuring a Data Flow, at step “Configure Mapping”, hover over the Auto Mapping icon. 
  2. In the info bubble that appears, click Undo Auto Mapping.
     
     
     The mapping for this field will not be remembered for the next import anymore, and instead the default suggestion will be offered if available. However, if you change the mapping again to something other than the default suggestion, it will be remembered again for the next import.
      
• To remove all saved mappings in one go: 
  1. In the Data Importer Settings, at “Clear Mapping Preferences”, click Clear Mapping for the Connection where you want to remove all mapping data.
     In the next import, default mapping suggestions will be shown instead of your previous mappings. Any new mapping changes you make will be remembered again for future imports.