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Best Practices for using Data Migrator


1. Please ensure that the source and target schema are exactly same. This can be achieved by refreshing your developer org from the production org. If the schemas are not exactly same, the migration may not succeed.

2. Data sets allow you to create "selective data constraints". It is important to know how many records a particular data set will return. This can be quickly predicted by hitting the "Count Records" button on the data set.6. This will ensure that you are not pulling in more records than necessary.

3. Before executing a sequence, it is always a good idea to "Dry  run" the sequence. It will accurately inform you about the number of records that will be migrated at each step. This will ensure that the sequence will not retrieve a large number of records before you execute the sequence.

4. The top-down approach gives you full control of your sequence. You can select the records to be used at every level and the columns to be used at every level.

The bottom-up approach gives you less control, but is a simpler way to create and execute than the top-down approach.

5. It is best to shutdown a variety of services before using Data Migrator. These services include the following:

  • Email Services (so that no email is sent to customers, employees or partners)
  • Apex Triggers
  • Workflows emails
  • Integration with external services

6. The Data Migrator should be installed in the production org, not in your full data sandbox. There are two reasons for it:

A. Data Migrator creates templates that need to be moved again and again. If the full data sandbox is refreshed, the templates will be wiped out.

B. Data Migrator has an in-built validation check. It does not allow the migration of the data to the same org. If the data migrator is installed in production, it will automatically ensure that you are not updating any of the records in your production org.

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