Copying of Salesforce objects with relations is a great feature. But this does not support Einstein datasets to be copied from one org to the other. It is critical for teams to have Einstein dataset in the lower orgs for development and testing

Salesforce doesn't support the creation or update or standard Order records with a Status Category of Active. This means Gearset is unable to data deploy any active orders. It would be very useful if there was an option for Gearset to temporarily set active orders to a draft status for the deployment or the Order Records and related Order Records, and then set the status back to Active for the final step.

We have some custom objects that hold financial data so masking currency and Percent fields will help when doing data deployments

Ability to build sequence of data load (choose a list of data load templates and have to possibility to run them automatically in sequence). The sequence can be changed.

There's no opportunity to save the data deployment settings after selecting objects and fields, and this can be quite time consuming, so if the job fails due to auth or other issues, right now, this requires the user to start over, and re-select objects and fields.

1) Currently PBEs are incorrectly inserted with the company currency as apposed to the currency of the source record.

2) PBE's currency cannot be updated once created (SF restriction) but because PBE's should not be referenced by Id, (that would be a terrible design decision). It is quite possible to delete and recreate any out of sync records.

Examine changes to Email Footers and allow deployment of changes.

This would be very helpful in order to communicate and set expectations with others on how long Data Deployments take as well as seeing how to improve the speed of longer running Data Deployments. If only one date/time can be displayed, then I think it would be better to see the End Time of the Data Deployment job. Currently, the Date column listed appears to be either (1) the start time of the Data Deployment job, or (2) the date/time when the Configure and deploy was clicked to start configuring the job. If it's #2, this isn't very useful.

Right now, using the data masking feature for data deployments, the values for country and state are real values and random. There's no guarrantee that the country and state will be valid pairings.

This causes issues for orgs that use the standard Country/State picklists from Salesforce.

The goal would be that the masking feature would pull from the Saleforce default values and make sure that the state and country are valid pairings as opposed to randomizing both separately

Currently, when doing a data deployment Gearset will let you know of all the referenced objects from the object you selected. What it doesn't do is the opposite of that - let you know all the objects that reference your object with a lookup.

It'd be great if we could add a filter to utilize some data pulled in a fetch/query during data deployment.

ex. field (TeamMember.Project_Lookup__c in {returned Project results in query in previous step of data deployment).

When deploying Data, it would be nice to be able to set field values. It could be just to null them or set a value. It could be part of the configuration or data masking.

It would be very helpful if we could deploy data from a local repository. We have different namespaces for internal packages and it would make data migration significantly easier if we could do it from a local machine where we'd switch the namespaces.

Staging environments typically exist with integrations with other systems that have references to auto-number fields
Data deployment re-evaluates auto-number fields instead of keeping the values of the source.

If data deployment jobs could automate the following it would probably work
1. changing the type of the auto-number field to text in the target org
2. potentially removing apex references to the field
3. deploying the data
4. rolling back metadata modifications in steps 1 and 2

"Select reference fields to deploy"

Ability to edit the value for the target deployment data for the reference field instead of searching for the match on the Target.

Ex. Loading Opportunities from a Source to a Target that contains 5 different record types, but when uploaded to the Target we specify the recordtypeid to one that matches a recordtypeid on the Target for the entire data load.

Similar to how the Owner reference can ignore the Target's users and default to the running user of the data deployment.

New users are often created in the production org that need to be monitored and brought back to sandboxes as well. It would be great if the data deployment tool could support moving user records from prod to sandboxes or scratch orgs.

When deploying data records from production to sandbox, the default matching criteria for the owner field will not typically work...

Gearset currently matches on email and profile, but the email addresses for users get modified in sandboxes. So, no match is found for users other than the one who created the sandbox.

It would be great if the first check was: does the user record id match. If not, use email + profile, if not, use the current user.

Currently when a data deployment template is created, there is no way to edit the template after it is saved so that components can be added or removed. It would be helpful if we could modify the components in the template without having to create the template from scratch again.

Much like the problem analyzers for metadata deployments in Gearset, it would be great if you could add a problem analysis feature for data deployments after having configured what you want to deploy.

Some scenarios will almost certainly cause the data deployment to either totally fail or only partially deploy some of the records and skip records it can't deploy. Providing automatic fixes (e.g. choosing not to include duplicates) would improve the number of deployments that work 100% of the time.