Before migrating legacy data, the first question is usually not “how do we export it?”

A common mistake is assuming that everything in the old system must be moved exactly as it is. In reality, some data is still operationally critical, some is only historical, and some exists because of old process baggage that should not survive into the new system.

If the target scope is not clarified first, the migration expands unnecessarily and the team spends too much effort preserving low-value history in production shape.

Older systems usually contain inconsistent field usage, patched states, missing timestamps, duplicate identifiers, and broken relationships accumulated over time. The export itself may be easy while the interpretation is messy.

That is why migration should include a real data audit: abnormal values, null patterns, duplicates, state mapping, and cross-table integrity. Without that work, the biggest surprises often appear on the cutover night itself.

Migration plans often describe only the happy path. A steadier plan also defines what happens if validation fails, key modules behave unexpectedly, or business teams find critical mismatches after cutover.

Rollback conditions, phased switching, temporary manual handling, and post-cutover verification should be part of the plan from the beginning. That reduces pressure and keeps one bad batch from turning into a full operational freeze.