Deploying relational data between Salesforce orgs can be challenging when you’re navigating how and when Salesforce record IDs change. If you’re not careful, you may end up with duplicate records… and a lot of extra work.
In this blog, we discuss when record IDs are modified during a migration and when they remain the same. We also explain how to prevent duplicate data records with Prodly.
Salesforce assigns a unique record ID to each record when you import it into an org.
It doesn’t matter whether you import it using manual entry, a simple single-object data loader, or a sophisticated data migration tool like Prodly.
Salesforce breaks the association between orgs. When you move a data set from one org to another, Salesforce assigns a new record ID to each record in the data set. Think, for example, of when you move data from sandbox to production or from production to sandbox.
There are also instances in which record IDs remain the same because Salesforce copies them, for instance when you:
Even when it copies record IDs, Salesforce still breaks the association of the records between orgs. Because the orgs aren’t synced, changes in one org after the refresh will not be reflected in the other.
When you move updated data from a sandbox to your production org, Salesforce assigns a new record ID to each record. If you haven’t taken any precautions against duplication, Salesforce inserts the data set from the sandbox without updating any of the old records in production.
Many Salesforce admins get frustrated with the process of deploying data between orgs without creating duplicate records.
Oftentimes, they assign external IDs to each object in a data set to associate the object with a parent object outside Salesforce. If you’ve used this technique before, you know it’s laborious, time consuming, and prone to error.
Prodly eliminates this time-consuming manual task with its exclusive Record Match feature.
When you migrate data, the Record Match manager automatically creates an association between source and destination org Salesforce record IDs. It then stores this information in the Prodly app. This eliminates the need to manually create and maintain formal external IDs on every record. And that saves you a lot of time and work.
When you deploy data between orgs, Prodly first checks to see if the source records have a matching record with the same Salesforce record ID in the destination org.
If there isn’t a match, Prodly checks its record match database to see if the records are the same but the IDs are different. If Prodly doesn’t find a match, it creates a new record. This prevents duplicates during a data deployment.
It’s best to set up the record match manager when you move data from an existing org to an empty one, from a sandbox to a production org, or after a sandbox refresh.
However, you can still set up record match during a development cycle. This involves a few extra steps to consolidate data and ensure the Record Match manager accounts for all the matching records.
Learn more about setting up the record match manager and about record match in general on our help site.
Successful relational data deployment starts with understanding when Salesforce record IDs change and when they’re copied.
Prodly takes matching and changing Salesforce record IDs into account when you deploy relational data with the record match manager. This solves the problem of duplicate data records without extensive use of external IDs. See how easy it is to deploy CPQ data with Prodly—request a demo today!
No, custom objects receive new IDs in the target org because Salesforce generates unique IDs for each record in an org. To maintain the relationships between data, you need a solid mapping strategy to link the new IDs with their corresponding records in the original org.
When migrating relational data like CPQ data, you also have to migrate related records to maintain their associations. This means you have to carefully map the old record IDs to the new ones in the target org to preserve relationships like lookups.
To prepare for record ID changes, plan the data migration carefully. This can include mapping existing relationships, or, to save yourself a ton of work, using Prodly to prevent the creation of duplicate record IDs.
Deploying relational data between Salesforce orgs can be challenging when you’re navigating how and when Salesforce record IDs change. If you’re not careful, you may end up with duplicate records… and a lot of extra work.
In this blog, we discuss when record IDs are modified during a migration and when they remain the same. We also explain how to prevent duplicate data records with Prodly.
Salesforce assigns a unique record ID to each record when you import it into an org.
It doesn’t matter whether you import it using manual entry, a simple single-object data loader, or a sophisticated data migration tool like Prodly.
Salesforce breaks the association between orgs. When you move a data set from one org to another, Salesforce assigns a new record ID to each record in the data set. Think, for example, of when you move data from sandbox to production or from production to sandbox.
There are also instances in which record IDs remain the same because Salesforce copies them, for instance when you:
Even when it copies record IDs, Salesforce still breaks the association of the records between orgs. Because the orgs aren’t synced, changes in one org after the refresh will not be reflected in the other.
When you move updated data from a sandbox to your production org, Salesforce assigns a new record ID to each record. If you haven’t taken any precautions against duplication, Salesforce inserts the data set from the sandbox without updating any of the old records in production.
Many Salesforce admins get frustrated with the process of deploying data between orgs without creating duplicate records.
Oftentimes, they assign external IDs to each object in a data set to associate the object with a parent object outside Salesforce. If you’ve used this technique before, you know it’s laborious, time consuming, and prone to error.
Prodly eliminates this time-consuming manual task with its exclusive Record Match feature.
When you migrate data, the Record Match manager automatically creates an association between source and destination org Salesforce record IDs. It then stores this information in the Prodly app. This eliminates the need to manually create and maintain formal external IDs on every record. And that saves you a lot of time and work.
When you deploy data between orgs, Prodly first checks to see if the source records have a matching record with the same Salesforce record ID in the destination org.
If there isn’t a match, Prodly checks its record match database to see if the records are the same but the IDs are different. If Prodly doesn’t find a match, it creates a new record. This prevents duplicates during a data deployment.
It’s best to set up the record match manager when you move data from an existing org to an empty one, from a sandbox to a production org, or after a sandbox refresh.
However, you can still set up record match during a development cycle. This involves a few extra steps to consolidate data and ensure the Record Match manager accounts for all the matching records.
Learn more about setting up the record match manager and about record match in general on our help site.
Successful relational data deployment starts with understanding when Salesforce record IDs change and when they’re copied.
Prodly takes matching and changing Salesforce record IDs into account when you deploy relational data with the record match manager. This solves the problem of duplicate data records without extensive use of external IDs. See how easy it is to deploy CPQ data with Prodly—request a demo today!
No, custom objects receive new IDs in the target org because Salesforce generates unique IDs for each record in an org. To maintain the relationships between data, you need a solid mapping strategy to link the new IDs with their corresponding records in the original org.
When migrating relational data like CPQ data, you also have to migrate related records to maintain their associations. This means you have to carefully map the old record IDs to the new ones in the target org to preserve relationships like lookups.
To prepare for record ID changes, plan the data migration carefully. This can include mapping existing relationships, or, to save yourself a ton of work, using Prodly to prevent the creation of duplicate record IDs.