What role does data migration play in cutover planning, and how do you mitigate its risks?

Data migration is frequently the single highest-risk element of a cutover, since it involves moving, transforming, and validating potentially millions of records from legacy structures into the new system's data model — and unlike configuration issues, a bad data migration can be genuinely difficult to detect until business processes actually start running against the migrated data.

flowchart LR
    A[Legacy data] --> B[Extract/Transform/Load]
    B --> C[Validation: reconciliation against source]
    C --> D{Validation passed?}
    D -->|Yes| E[Data ready for cutover]
    D -->|No| F[Remediate and re-run before cutover]

Mitigation centers on running multiple full migration dry runs well before the actual cutover (not just testing the migration logic once), building rigorous reconciliation checks comparing migrated data against the source system record-by-record, and involving actual business users in validating that migrated data looks and behaves correctly from a functional perspective, not just a technical "did the load complete without errors" check.