ERP Data Migration & Reconciliation
Move ERP data with reconciliation built into the migration.
Control ERP data transition through explicit scope, mapping, cleansing, trial loads, validation and financial reconciliation—not record counts alone.
- Baseline and scopeProfile the source and approve what moves.
- Map and cleanseVersion target meaning and transformation rules.
- Trial and validateRepeat loads and own every material exception.
- Reconcile and sign offVerify business state before cutover acceptance.
When loading records is not enough
Start with business meaning, acceptance and the source baseline.
A controlled migration makes every scope, mapping and exception decision visible before finance or operations is asked to trust the target system.
- Source master data, open transactions and history contain inconsistencies that cannot be carried forward blindly.
- Source and target structures represent accounts, dimensions, customers, items or transaction state differently.
- Finance needs evidence that balances and operational meaning remain correct after transformation.
- Trial loads are finding exceptions, but ownership, disposition and acceptance criteria are unclear.
Migration scope
Define the data decision and its acceptance evidence.
Data decision
Define what migrates, what remains accessible, what is archived and what is retired for each company, domain and historical period.
Mapping and cleansing
Make source-to-target meaning, transformation rules, defaults, enrichment and exception treatment explicit and reviewable.
Reconciliation and acceptance
Agree control totals, representative records, financial tie-outs, exception thresholds and accountable sign-off before cutover.
Migration controls
Make transformation, exception handling and sign-off reproducible.
Baseline the source
Profile completeness, duplicates, invalid values, balances and extract timing so the migration starts from a known state.
Transform deterministically
Version mappings and transformation rules so each target value can be traced to its source and approved decision.
Learn through trial loads
Repeat representative loads, retain rejected records and assign every material exception a disposition and owner.
Reconcile business state
Compare balances, control totals, relationships and representative transactions instead of treating matching record counts as acceptance.
Data migration method
Move from a known source to a reconciled target.
Profile
Inspect source data, constraints, quality patterns and extraction boundaries.
Scope
Approve migration, retention, archive and retirement decisions by data domain.
Map
Define target meaning, transformation, cleansing and exception rules.
Trial
Run repeatable loads and investigate rejected, missing, duplicated or changed records.
Reconcile
Tie control totals and representative business state back to the accepted baseline.
Cut over
Execute the final load with entry criteria, checkpoints, sign-off and a documented recovery decision.
Migration outputs
Leave a traceable path from source scope to cutover sign-off.
- Source inventory, profile and approved migration scope
- Source-to-target mapping and transformation specification
- Cleansing rules and owned exception backlog
- Trial-load results with repeatable validation evidence
- Financial and operational reconciliation workbook
- Cutover, sign-off and recovery runbook
Next step
Discuss your data migration and reconciliation needs
Describe the source, target, data scope and reconciliation concern already visible.