A safe Salesforce data migration follows five steps: profile the source for quality and duplicates, agree a written field map, dry-run the load into a sandbox, reconcile row counts and key values against source, and write a rollback plan before the production cutover.
Key takeaways
- Profile before you map — you cannot map data you have not measured.
- Every migration gets a sandbox dry run and a row-level reconciliation.
- Preserve legacy IDs so historical references keep resolving.
- A cutover without a rollback plan is a hope, not a plan.
1. Profile the source
Count records per object, measure field fill rates, and find the duplicates before anyone writes a mapping spreadsheet. Profiling routinely halves the volume people expected to migrate.
2. Agree the field map
A field map is a contract. It names every source field, its destination, its transformation, and what happens when the value is missing. Anything unmapped is a decision someone will make under pressure at 2am otherwise.
3. Dry run in a sandbox
Load the full volume, not a sample. Volume exposes governor limits, timeout behaviour and validation-rule collisions that a hundred-row test never will.
4. Reconcile
Row counts per object, sum totals for key numeric fields, and spot checks on the twenty most valuable records. Sign the reconciliation report before cutover.
5. Plan the rollback
Know what "abort" looks like: which loads reverse, which stay, who decides, and by what time. A rollback plan you never use is the cheapest insurance in the project.
Frequently asked questions
Should we migrate all historical data?
Usually not. Migrate what is operationally useful and archive the rest — dead data slows every future release.
How long does reconciliation take?
For a typical SMB dataset, a day. It is never the step to compress.
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