How to prepare business data for an ERP migration

Data migration is a business decision about what the new ERP should trust. Moving every old record can carry duplicates and weak definitions into the new system. A controlled migration chooses relevant information, assigns accountable owners and reconciles each load against approved source totals.

Choose what needs to migrate

Separate master data, opening balances, open transactions and historical records. Decide how much history users genuinely need for daily work and what can remain in a secure archive. A smaller, purposeful scope is easier to cleanse, test and reconcile.

Assign a business owner to each dataset

Customers, suppliers, items, accounts and employees should each have an owner who understands the meaning of the fields. Technical teams can transform files, but business owners must decide which duplicate is correct and which record is still active.

Clean and standardise master data

Resolve duplicate names, incomplete contacts, inconsistent units, invalid tax details and unused records. Establish naming and coding rules for the future. Migration is an opportunity to improve governance, not just a one-time exercise before launch.

Map source values to the new model

Document how accounts, warehouses, units, statuses and categories translate. Record defaults and transformations clearly so the result can be repeated. Avoid silently forcing unmapped values into a generic category because that weakens reporting from the first day.

Rehearse the migration

Run at least one full trial using the same extraction, transformation and loading steps intended for cutover. Let users inspect records and complete working scenarios. Measure timing, correct errors and repeat until the process and result are predictable.

Reconcile before acceptance

Compare record counts, control totals, receivables, payables, inventory quantities and financial balances. Investigate every material difference and retain evidence of approval. A file loading without a technical error does not prove that the business data is complete or correct.

Protect quality after go-live

Limit who can create or change key records, define required fields and review duplicates regularly. Data governance after launch protects the investment made during cleansing and helps integrations and reporting remain reliable as the business grows.

Practical checklist

• Approved migration scope
• Owner for every dataset
• Documented mapping rules
• Completed trial migration
• Signed reconciliation totals
• Post-launch data governance