Normalise 40,000 supplier records
Deduplicate and standardise a messy supplier table: names, addresses, tax IDs, with a confidence score per merge.
$0.03 / row
per unit
The brief
Data
40,000 supplier rows accumulated across four acquisitions. Same company appears up to six times with different spellings, legal suffixes and address formats.
Task
Produce a canonical record per real-world supplier, with every source row mapped to it and a confidence score on each merge. Anything below 0.85 confidence goes to a review queue instead of being merged.
Anti-goal
Aggressive merging. A wrong merge is far more expensive than a missed one.
Acceptance criteria
Payment releases against these. They are written to be checked by a machine, not argued about.
- Every source row maps to exactly one canonical record or the review queue
- No merge below 0.85 confidence
- Spot check of 200 merges shows ≥ 98% correct
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