Data Migration Explained: Eight Stages, Key Terms, and Where Most Projects Fail

Data migration is the process of moving a client's records from an old system to a new one, ensuring all data arrives complete, connected, and accurate. The work spans eight defined stages — from kickoff and source profiling through field mapping, cleaning, dry runs, user testing, cutover, and hypercare — each separated by a formal checkpoint called a gate. Key terminology includes concepts like field mapping, transformation, reconciliation, and orphan records, which professionals encounter in virtually every migration project. The messiest migrations tend to involve replacing spreadsheets, since unstructured user input means the data can contain almost anything. Two categories of failure account for most project pain, and understanding the difference between profiling (discovering what data actually exists) and reconciliation (proving the move worked) is central to avoiding them.