Data migration without surprises: validate early, reconcile often

Migrations rarely fail because data cannot be moved. They struggle because the data turns out to be different from what everyone assumed: duplicates, gaps, inconsistent formats and rules that live only in people's heads.

Assess before you map

Profiling the source data early shows what you are really working with. The findings should inform the target design and the cleansing plan, rather than arriving as surprises during testing.

Make validation a business decision

Validation rules define what good data looks like in the new system. They need input from the people who use the data every day, and clear owners for resolving exceptions.

1. Assess and profile source data
2. Agree mapping and validation rules with data owners
3. Run repeatable rehearsals with automated checks
4. Reconcile counts, values and key relationships every time
5. Cut over against agreed acceptance criteria

Reconcile at every rehearsal

Each trial migration is a chance to prove the process. Reconciling record counts, key values and relationships on every run builds confidence and gives a clear, evidence-based go or no-go decision at cut-over.