Data migration is the process of moving records from old systems into a new CRM or ERP. The rule that decides success is simple: clean the data first and move it second. Define scope, remove duplicates, map fields, run trial migrations with business sign-off, and rehearse the cutover before go-live.
Why do migrations go wrong?
New systems expose old problems. Duplicate customers, inconsistent product codes, missing fields and years of unused records are invisible in spreadsheets but become obvious in a structured system. Teams then blame the software, when the cause was never fixed in the source.
Step 1: Decide what to move
Not everything deserves migration. Active customers, open orders, current prices and recent transactions usually do. Old, closed or low-value records can be archived in a read-only form and searched when needed. A smaller, cleaner dataset makes the new system faster and the project cheaper.
Step 2: Profile and clean
Count records and find blanks in required fields.
Deduplicate customers, suppliers and products using agreed matching rules.
Standardise formats for names, phone numbers, countries and units.
Assign an owner for each data set who can decide what is correct.
Step 3: Map fields
Create a mapping sheet that lists each old field, the new field, the transformation and the owner. This single document prevents most arguments later. Pay particular attention to statuses, tax and currency fields, and any custom fields that carried unwritten rules.
Step 4: Run trial migrations
Migrate a sample, then the full set, into a test environment. Business users should check real examples: a customer, an open quote, a stock item, an unpaid invoice. Record issues, fix them in the source or the mapping, and repeat until the results are stable.
Step 5: Plan the cutover and the rollback
Agree a freeze period when users stop changing old data, a final migration window and a checklist of validation steps. Keep the old system available read-only for a defined period, and know in advance what would trigger a rollback.
Key takeaways
Migrate less, and migrate it cleaner.
Use a field mapping sheet with named data owners.
Rehearse with trial migrations and business sign-off.
Frequently asked questions
How long does data migration take?
It depends on data volume and quality, but cleaning and validation usually take longer than the technical transfer. Plan for several trial runs rather than one.
Should we migrate all historical data?
Rarely. Move active and recent records, and archive the rest in a searchable read-only form.
Who is responsible for data quality?
The business. Technical teams can move data, but only the people who use it can confirm what is correct.
Consulteq supports requirements, data planning and delivery oversight through its consultation and project management service, or speak with a Consulteq consultant in Dubai.