Running your first data deployment

How to deploy seed sandboxes or move data between Salesforce orgs

Tom Smith avatar
Written by Tom Smith
Updated over a week ago

Before you can run a data deployment, you must manually enable Gearset's data loader. Running a data deployment in Gearset is a quick and simple process:

Select source and target

  • Select the source and target orgs to be used and click CONFIGURE DEPLOYMENT. The orgs must be owned by your username and authenticated by OAuth, and not username/password.

  • You can also deploy data to and from Salesforce DX scratch orgs. To find out how to configure and create scratch orgs within Gearset, see our support guide. However, you will not be able to select a delegated org for deploying data.

Select primary objects to deploy

Gearset will now perform a Salesforce listMetadata call to retrieve the object list from the selected source and target organizations, and display the results in a tree view.

  • For each parent object in the tree, you can specify the number of records to retrieve, up to a maximum of 100,000.

  • When a parent object is expanded, which you can do by clicking on it, Gearset checks for and lists any dependencies that are detected that can then be included within your data subset. 

  • Gearset will then traverse the dependency graph to determine any further indirect dependencies (up to 15 levels) necessary to deploy records from the selected objects.

  • Use the object filter Configure filters settings to customize your data set and retrieve and deploy records based on the field value.

  • Use the Filter using parent object to further filter the records to deploy, by restricting it based on the parent object.

    • For the example below, if we tick the Only deploy ... children of Accounts.Contacts - this will only include children of the selected Accounts that ALSO have .com in the Email field. Most likely this will be less than the 16 records displayed that match the Contact object filter.

  • Once the objects have been selected, click NEXT.

Select matching configuration and related objects

  • Choose how you want to match existing records, which related objects to include (this is determined by lookup and master-detail fields see this article for more info), and customize their field mapping for upserting.

  • Note that if the linked orgs are RelatedOrgFullDeployment orgs (e.g. sandboxes and production orgs, but not developer orgs), then, in addition to the "Create new records" and "Upsert records" deployment methods, there is also a "Don't deploy" option. This option will not deploy any records for the selected object, with Gearset assuming that the records are already on the target org.

  • The field chosen to match records for upserting can be an External ID field or an ID Lookup field. (You can create a custom field with the External ID property, and view this in Salesforce. The ID Lookup property is visible only via the API in Workbench.) If neither of those types of fields exists, new records will be created.

  • You can upsert with ID when any of these are true:

    • The source is "backup" and the target is the original org.

    • The source is the same org as the target.

    • The source is a sandbox, the target is a sandbox, and they're sandboxes of the same org.

    • The source is a prod org, the target is a sandbox, and the target is a sandbox of the source org.

  • Choose whether you'd like the data deployment to continue if it hits an error deploying a record. In that case, if a deployment step fails, the remaining deployment steps will continue to execute, ignoring the errors encountered and deploying as many of the records as possible. Or, if you want the deployment to stop in the event of an execution step error, select the Stop deploying remaining records option.

  • By default, all the fields that belong to the selected objects will be deployed. If you would like to exclude certain fields from the deployment, you can click the arrow on the right side of the NEXT button and select Exclude fields.

    You will have the option to check the list of fields for each object, and you can simply untick the ones that you would like to leave out of the deployment.

  • Click NEXT to continue and configure data masking.

Select data masking options

  • Choose whether you want to mask any fields to obfuscate their values. If a field is masked, Gearset will deploy fake values instead of the real values for that field, concealing sensitive customer information. Learn more about data masking.

  • Once you've chosen which fields to mask, click PRE-DEPLOYMENT SUMMARY to review the data to be deployed. Gearset will create and list out the steps we’re about to take in your data deployment.

Deploy the data records

  • You'll be able to see the object records to be deployed, the actions Gearset will take to retrieve the records, such as fetching, including, creating and upserting, as well as the field count and any applied filters.

  • Click on DEPLOY DATA to deploy the selected data to the target org. When the deployment is running, each stage will mark as completed and show you how many records have been processed in each step.

  • If you're deploying to a production org, you'll be asked to confirm that you're happy to proceed before the deployment runs.

  • Once complete, you'll have your subset of data available for any testing and debugging you'd like to perform on the target org.

  • The deployment will be stored in your data deployment history in the app. From here, you can view previous data deployments, their status, and view the details of which records were moved. Learn more about data deployment history here.

Deploy Audit fields

By default, when deploying data from a source org to a target org, the Created Date and Last Modified Date of the new records will be set to the date of the deployment.

This can be problematic where users build reports analyzing data by Created Date.

However, if the "Create Audit Fields" permission is enabled in the target org, the user performing the deployment has this permission, and the Insert operation is used for the object during the data deployment, then inserting the Created Date and Last Modified Date is possible.

Using the Upsert operation does not allow the CreatedDate to be inserted.


  • If Gearset needs to do any additional updates later in the deployment i.e. updating lookup fields at the end of the deployment, then the LastModifiedByID and LastModifiedDate might become updated to be Gearset user doing a modification.

  • With these permissions, users can fill audit fields on record creation only through API tools. Future edits (updates) cannot be made.

Did this answer your question?