Data Migration Planning

Before mapping fields, teams should decide which records are authoritative, which history is required, how identities match, what can be archived, and who accepts each migrated domain.

Legacy values often encode exceptions and past process changes. Profiling representative and worst-case records is more reliable than assuming the documented schema describes actual use.

A migration specification should describe source, target, transformation, default, validation, ownership, and handling for invalid values. Cleaning can occur before extraction, during transformation, or through a governed exception process.

Silent coercion is dangerous. Rejected records and lossy transformations should remain visible and attributable.

Run migrations against production-like snapshots with measured duration and repeatable tooling. Verification should include counts, totals, referential integrity, sampled business workflows, permissions, files, and reports—not only successful inserts.

Rehearsals expose source drift, performance constraints, ordering, downtime, and manual exception volume while rollback remains inexpensive.

The cutover plan defines freeze or synchronization boundaries, final extraction, validation gates, communications, ownership, and go/no-go authority. Rollback must state what happens to changes created after cutover begins.

Parallel operation can reduce risk but creates synchronization and double-entry hazards. It should have a bounded purpose and exit date.

Migration copies are sensitive production data. Minimize access, encrypt transport and storage, define retention, and remove temporary extracts. Logs should identify failures without exposing protected values.

Legacy retirement includes access removal, retention evidence, contract and infrastructure changes, audit preservation, and confirmation that downstream integrations no longer depend on the old system.