Data migration services.
Move the data, keep all of it, and be able to prove it.
Data migration goes wrong quietly. Records that failed to import, fields silently truncated, dates parsed in the wrong format, duplicates created because the matching rule was too loose. The damage often surfaces weeks later when someone cannot find a customer's history. The defence is validation and reconciliation, not care alone.
What’s included
- Source analysis and field mapping
- Cleaning and de-duplication before import
- Transformation between differing data models
- Trial runs against a copy with full reporting
- Row-count and checksum reconciliation
- Verified cutover with a rollback plan
- Post-migration validation against the source
Reconcile, do not assume
After every migration I compare counts and key totals between source and destination, and produce an explicit report of anything that did not transfer and why. If you cannot prove the data arrived intact, you do not know that it did.
Clean before you migrate
Migration is the natural moment to remove duplicates and fix inconsistent formatting — but each of those decisions should be deliberate and reviewed by you, not silently applied by a script.
Common questions
How do we know nothing was lost?
Reconciliation reporting: row counts, key totals and an explicit list of records that failed with the reason. You get that report before we cut over.
Can you migrate from a system with no export?
Usually, via direct database access, an API, or scraping the interface where nothing else exists.
What if something goes wrong during cutover?
There is a rollback plan and the source system stays intact and available until we have verified the new one.
Have a project in mind?
Tell me what you're building and roughly when you need it. I reply to every genuine enquiry within one working day.