Adopt change data capture to keep sources and targets aligned while you migrate slices of functionality. Rehearse cutovers in production-like environments with masked datasets. Define clear rollback triggers. Success looks like customers never noticing the move, while teams confidently iterate on performance, quality, and lineage documentation afterward.
Inventory every consumer of legacy data: reports, nightly jobs, archival processes, and vendor interfaces. Visualize flows and SLAs. Replace fragile point-to-point connections with managed contracts, publish-subscribe patterns, and cataloged interfaces. This converts risky surprises into planned changes, reducing weekend firefights and avoiding painful regressions in downstream teams.
Build contract tests for APIs and schemas, synthetic transactions for critical paths, and data quality checks for completeness, accuracy, and timeliness. Automate performance baselines. When test evidence is part of each migration step, risk conversations shift from opinion to observable facts that support calm, confident cutovers.