Poor data quality can turn a technically successful migration into a difficult go-live. Using real examples from migration projects, we look at how missing records, conflicting criteria and hidden data relationships cause problems, and how a Data Quality Review helps identify them before the move.

Data migration usually gets one line on a project plan, then quietly becomes the reason the go-live date slips. On paper it looks simple: move the data from the old system to the new one. In practice, it’s where all the assumptions about “the data” meet what’s actually sitting in the source system.