Data migration & cleanup
A new system fed with messy data is still messy — it just fails faster. Before any build or migration, the data has to be cleaned, structured, and trusted. It is the unglamorous step that decides whether the whole project works.
You are not stuck because your data is bad
You are stuck because years of spreadsheets, inconsistent codes, and duplicate records were never meant to become a system. That is normal — and fixable, but it must be done deliberately, not by importing the mess into something new.
What this involves
01
Assess the source
We look at where data lives — spreadsheets, old systems, AutoCount — and how consistent it is.
02
Clean and structure
De-duplicate, standardise codes and units, fix gaps, and define a reliable structure.
03
Set a controlled starting point
Establish a clean baseline so the new system starts trusted, not compromised.
04
Migrate with validation
Move the data with checks, so errors are caught at the boundary — the same discipline as our system integration.
Why it comes first
Migrating dirty data into a custom ERP or new app guarantees mistrust on day one. A clean baseline is often the difference between a system staff rely on and one they quietly abandon. It is usually scoped during the system audit.
FAQ
Can you clean data without rebuilding everything?
Yes — cleanup and a controlled baseline can be a standalone first step before any larger build.
What sources can you migrate from?
Spreadsheets, legacy systems, and AutoCount are the common ones; we assess each case.
Why not just import what we have?
Importing dirty data carries the problem forward. Cleaning first is what makes the new system trustworthy.
Assess My Data