The match score is a numerical value that represents the degree of similarity between two column values. An algorithm calculates a match score as a decimal value in the range 0 through 1. An algorithm assigns a score of 1 when two column values are identical.
When you select multiple column pairs for analysis, the transformation calculates an average score based on the scores in the selected columns. By default, the transformation assigns equal weight to scores from each pair of columns. The transformation does not infer the relative importance of the column data in the data set.
You can edit the weight values that the transformation uses to calculate the match score. Edit the weight values when you want to assign higher or lower priority to columns in the data set.
You can also set the scores that the transformation applies when it finds a null value in a column. By default, the transformation treats null values as data errors and assigns a low match score to any pair of values that contains a null.
The algorithm you select determines the match score between two values. The algorithm generates a single score for the two values. The match scores do not depend on the type of match output or the type of scoring method you select.