How do you match legacy ERP records when there is no common identifier?

We compare combinations of available attributes, such as names, addresses, registration numbers and contact details. Different fields can use different comparison methods, with alternative rules for records missing particular attributes. The resulting matches need testing against known examples before consolidation.

Can you deduplicate ERP data without changing the source systems?

Yes. With WinPure, we can work on imported copies, investigate matches and prepare consolidated outputs while retaining the original source data. Writing results back is a separate, configured action. Your team can also export a mapping of source records to resolved entities for use in the migration.

Does a Golden ID replace the primary key in the new ERP?

A Golden ID provides a persistent reference for the resolved entity. Your ERP may generate its own primary keys, so the migration needs to preserve the mapping between legacy IDs, Golden IDs and target IDs. That mapping supports traceability and the reassignment of dependent records to the correct master.

What happens to invoices and orders when duplicate master records are merged?

The references attached to the original masters need to be mapped to the appropriate surviving record. Consolidating a supplier does not automatically update every invoice or purchase order in your ERP. We retain the source references needed to support that work; your migration tooling applies the mappings when loading the dependent data.

How should new and updated records be handled after the initial cleanup?

Subsequent extracts need to distinguish new entities from changes to existing ones. We can reuse saved cleaning and matching configurations and compare incoming records against established entities. The extraction design must also capture relevant updates and deletions, since a newly created record and a changed address require different treatment.

Can fuzzy matching resolve records with missing identifiers?

It can help where other populated attributes provide sufficient evidence. However, a similarity algorithm cannot infer a missing identifier simply by lowering the threshold. We assess which remaining fields can support the comparison and keep uncertain results separate for investigation.

Where does WinPure fit alongside an ERP migration or ETL tool?

We support the profiling, cleaning, matching, entity resolution and consolidation of the data being prepared. Your migration or ETL tooling handles the destination specific loading, including target mappings, transaction dependencies and ERP validation. The prepared records and identity mappings connect those two parts of the work.

Data Quality

Practical guidance on data cleansing, matching, and identity resolution - from the team building the tools.

All Product Updates Data Quality Data Matching Data Cleansing CRM Data Entity Resolution Data Match Algorithms

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