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ERP Data Migration

Source extraction, field mapping, undocumented logic and failed target imports delay ERP projects. Beetl handles the data path so the programme keeps its date.

Where this starts

First scope
One source ERP, one target ERP, one bounded entity group
Output
Reconciled, target-ready data with reconciliation totals
Not in scope
ERP configuration, process redesign, cutover management, accounting policy, end-user training

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 plans budget for design workshops, testing and training. They rarely budget for the weeks lost to extracting legacy data, working out what the fields mean, and fixing three unrelated things before the target accepts a load.

The usual blocker is undocumented logic: a field filled by a customisation written years ago, a value that means one thing in one plant and something else in the next, a supplier that exists twice after a merger nobody unwound. None of it shows in the source schema.

We treat the data path as its own workstream. We read the legacy source as it stands, write mappings and rules as SQL and mapping tables instead of a hand-kept spreadsheet, and reconcile the output before it goes anywhere. Failures turn up on our side, not in the target's error log.

We take one entity group at a time: customers, suppliers, products, chart of accounts, open orders, or open receivables and payables. ERP configuration, process redesign, cutover, accounting policy and training are not ours. The data path is, and it is usually the part with the least clear owner.

  • The mapping lives in a spreadsheet that three people have edited and nobody trusts.

  • The target rejects a load, and the team can only find the failed records by opening them one by one.

  • Logic that matters sits in an old customisation nobody documented, and its author has left.

How we work

One bounded entity group at a time. Each one is extracted, mapped, validated, and reconciled before the next is opened.

  1. 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.
  2. 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.
  3. 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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