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Configuring the tFuzzyJoin component

Availability-noteDeprecated

Procedure

  1. Double-click tFuzzyJoin to display its Basic settings view and define its properties.
  2. Click the Edit schema button to open a dialog box that displays the data structure of the input files and then define the data you want to pass to the output components, two columns in this scenario, IdClient and Email.
  3. Click OK to close the dialog box.
  4. In the Key definition area of the Basic settings view of tFuzzyJoin, click the plus button to add two columns to the list and then select the input columns and the output columns you want to do the fuzzy matching on from the Input key attribute and Lookup key attribute lists respectively, IdClient and Email in this example.
  5. Click in the first cell of the Matching type column and select from the list the method to be used to check the incoming data against the reference data. In this scenario, Levenshtein is the matching type to be used.
  6. Then set the minimum and maximum distances. In this method, the distance is the number of character changes (insertion, deletion or substitution) that needs to be carried out in order for the entry to fully match the reference. In this example, we want the minimum distance to be 0 and the maximum distance to be 2. This will output all entries in the IdClient that exactly match or that have maximum two character changes.
    Information noteNote:

    You can create and store context variables for the minimum and maximum distances in order to start from a low max number to match rows and go up to higher max number to match more possible rows. You can press Ctrl+Space to access the variable list and select these new context variables. For more information about context variables, see Using contexts and variables.

  7. Set the matching type for the second column to be checked, Metaphone in this example. There is no minimum nor maximum distance to set because this matching method is based on phonetic discrepancies between the input main and reference data.
  8. Select the Inner join (with reject output) check box to define one of the outputs as inner join reject table.

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