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.

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.

Allow complex filters and child relationships on filters for data loading. For example, filter the Account to only load if the Owner is an Active user in the system.

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.

It would be great to be able to pick the batch size used when doing data deployments.

We have to work with some orgs using poorly performing managed packages that are blowing up due to CPU limits.

We don't have many option, so being able to reduce the batch size, and hence the CPU load would be really useful.

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.

Please add the ability to use the "Compare and Deploy" for Attachments and Files. The ability to migrate PDFs, image files, word docs, and excel spreadsheets would be GREATLY appreciated! Thanks!

Datapacks / Vlocity Metadata

During a data deployment it should be possible to mask the data in specific fields. For example, if I were importing Account and Contact data from production into a sandbox I would want to be able to mask email address so that we can't erroneously send actual customers emails while we're testing

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.

The current data deployment functionality works fine for one-off deployments, but if you are trying to keep specific data in sync across multiple orgs, the ability to schedule data deployments for a given time in the future would let you deploy on a recurring basis automatically. Becomes especially helpful when combined with the current data filtering options.

When deploying data records, it would be helpful if audit fields values could be migrated

Provide options to delete records from Target Org. This will help clean up of test data and reload from Source.

When we pull down a version between our local and staging environments. We would like to also automatically pull in the testing data from another project.

As one of the things we are trying to setup is taking a version from Prod then running GhostInspector through our core flows. Ideally every 4 hours we take a backup from metadata + locked down actual data. Then run tests against it.

Show source Org records count for each object so that we can decide on how much of it can be moved and how much of filter is needed. Moreover after all object are select with filters for movement, please show the total number of records that will be migrated across all selection and its related objects. This will tell us if we are exceeding the limit of 10000 and do we need to split.

It would be useful to select all objects in the data deploy screen to make it faster to select a large number of objects (even better would be the ability to group objects and select whole groups at once)