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Functional & Business Analysis

Hire Data Migration Specialists

Specialists for the part of a go-live that decides it — extraction, cleansing, load and the reconciliation that proves it worked.

Data migration is the part of a cutover most likely to be underestimated and most likely to stop a go-live. It is scheduled as a task and behaves like a project, because the real work is not moving the data — it is discovering what the data actually contains.

Profiling first is the whole discipline. Not what the field is called, but what is in it: how many customers have no country, how many part numbers carry a suffix the new system will not accept, how many open orders reference a supplier that no longer exists. Every one of these becomes a decision the business has to take, and taking them in week two is a conversation while taking them in cutover week is a delay.

The load has to be repeatable. It will be run for a mock, run again after the mapping changes, run again in the dress rehearsal, and run once for real. A load that appends rather than matching on a business key produces duplicates on the second run, and duplicates in master data are still being cleaned up a year later.

Then reconciliation, which is what actually gets signed. Counts by object, values by control total, and a documented explanation for every deliberate difference — records intentionally not migrated, balances rounded, history truncated at an agreed date. Without that, nobody can say on the Monday whether the migration worked, and the argument is unwinnable in either direction.

What these engineers do

  • Profiling the source before anyone agrees a mapping, so the surprises come early
  • Cleansing and de-duplication rules the business owns rather than IT inventing
  • Load design that is repeatable and idempotent, because it will be run more than once
  • Reconciliation by count and by value, signed off against the source system
  • Mock loads, dress rehearsals and a cutover plan with a defined point of no return

Delivered AI-first

Specialists use AI assistance to profile and classify large source datasets, draft mapping and transformation logic, and generate reconciliation queries. Every figure a business signs off is verified against the source by a person.