01
Extract and keep the source as it is
The legacy system is read as it stands, and a source-faithful copy is retained. When a mapping is questioned six weeks later, the original record is still there to check.
← Use cases
ERP migration
ERP Data Migration
Source extraction, field mapping, undocumented logic, and failed target imports are what delay ERP projects. Beetl handles the data path so the programme keeps its date.
Source systems
Legacy ERP
Database exports
Files and spreadsheets
Vendor and customer masters
Undocumented side systems
Beetl answer
Reconciled, target-ready data
Problem signals
ERP programmes are usually well managed on configuration and badly exposed on data. The plan accounts for design workshops, testing, and training. It rarely accounts for the weeks that disappear into extracting the legacy data, working out what the fields actually mean, and discovering that the target will not accept a load until three unrelated things are fixed.
The recurring blocker is undocumented logic. A field is populated by a customisation written years ago. A value means one thing in one plant and something else in another. A supplier exists twice because of a merger nobody unwound. None of that is visible from the source schema, and all of it has to be resolved before the target will take the records.
Beetl treats the data path as its own workstream. The legacy source is read as it stands and kept in a source-faithful form. Mappings and business rules become explicit SQL and mapping tables rather than a spreadsheet somebody maintains by hand. Validation and reconciliation run against the prepared output before it goes anywhere, so failures are found on our side rather than in the target's error log.
The engagement is scoped to one bounded entity group: customers, suppliers, products, chart of accounts, open orders, open receivables and payables. Beetl does not own the ERP configuration, the process redesign, the cutover, the accounting policy, or the training. The data path is the part we take, and it is usually the part with the least clear owner.
1
Mapping decisions live in a spreadsheet that three people have edited and nobody fully trusts.
2
The target rejects a load and the team cannot tell which records failed or why without opening them one at a time.
3
Business logic that matters exists only in a legacy customisation nobody documented, and the person who wrote it has left.
How the work runs
One bounded entity group at a time. Each one is extracted, mapped, validated, and reconciled before the next is opened.
02
Make the mapping explicit
Field mappings, value crosswalks, and the rules behind them become SQL and mapping tables you can read and review, rather than steps inside a migration spreadsheet.
03
Validate and reconcile before loading
Data-quality checks and reconciliation totals run against the prepared output, so problems surface before the target rejects a load rather than after.
What you are left with
Reconciled, target-ready data with the mapping decisions still legible, so the next entity group starts from evidence rather than memory.
- Target-ready data for one entity group, with reconciliation totals against the source.
- Mapping and business-rule definitions kept explicit and versioned, not buried in a workbook.
- A repeatable path for the next entity group, since the extraction and validation layer is already running.
Bring the entity group that is blocking your go-live.
Customers, suppliers, products, chart of accounts, open orders, open receivables and payables. Tell us the source ERP and the target, and we will scope one group.
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