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Overview

The Fuzzy Merge node is a transformation node in a Weave Workflow that combines and matches two data sets using a fuzzy matching algorithm, joining similar or related records rather than only exact matches to improve data accuracy during integration. It sits in the middle of a Workflow’s processing path between two source nodes (Data Import) and terminal nodes (Result, Output) and emits the merged data downstream.

The node is configured in two places: the node panel sets the Filter Algorithm and a Percentage threshold, and the Configure dialog defines the Matching Criteria and Fuzzy Merge Criteria. The merged output includes the joined columns from both data sets along with per-match score columns produced by the algorithm.

Note: “Workflow” is the in-UI term for what some Weave documentation calls a pipeline. This reference uses “Workflow.”

When to use it

  • Matching records across two data sets where keys are similar but not identical (typos, formatting differences, near-duplicates).
  • Joining two data sets on a combination of an exact key and one or more fuzzy-matched columns.
  • Producing a merged table with per-column match scores for downstream filtering or review.

Configuration

Node panel settings

SettingDescription
Filter AlgorithmThe fuzzy matching algorithm applied to the match [Levenshtein distance, Soundex Phonetic, Similarity Score].
PercentageA threshold value from 1 to 100 for the algorithm.
ConfigureOpens the Fuzzy Merge dialog where Matching Criteria and Fuzzy Merge Criteria are defined.

Configure dialog

The Configure dialog defines the criteria as rows. Each row pairs a column from the first data set with a column from the second via a join condition.

FieldDescription
DatasetThe source data set for the left and right side of the pairing.
ColumnThe column from each data set used in the match.
Join ConditionThe condition relating the two columns.
ActionAdd (+) a criteria row or delete an existing one.

The dialog has two sections: Matching Criteria and Fuzzy Merge Criteria.

Key behaviors

Fuzzy Merge is a transformation node. Unlike Data Import (source) and Result / Output (terminal), it sits in the middle of the Workflow, receiving two upstream inputs, matching them, and passing the merged result downstream.

Two-stage criteria. Configuration separates Matching Criteria from Fuzzy Merge Criteria.

Threshold-driven matching. The Percentage value tunes how close records must be to count as a match.

Scored output. The merged table carries per-column and aggregate score columns reflecting match strength, supporting downstream review or filtering.