Accelerate the Value of Data

Match cleansers

The cleansers provided by Reltio enhance the matching process.

Reltio provides the following out-of-the-box data transformation capabilities that you can apply within a match rule configuration to increase the effectiveness of matching:

  • Name dictionary cleanser - activates and controls synonym matching.
  • String replacement cleanser - finds a predefined substring in an attribute and replace it with another string of your choice.
  • Noise words removal function - eliminates unwanted noise words from an attribute during matching.
  • Value concatenator cleanser - takes an attribute that has multiple values and creates a string out of it.

All these capabilities perform their function only within the match framework and don't modify the actual data in the record. They must not be confused with Reltio's profile-level cleansers (like email, phone, and address cleansers) that actually modify the profile data. For more information, see Out-of-the-box Cleanse Functions.

The Name dictionary cleanser, String replacement cleanser, and Value concatenator cleanser are stand-alone cleansers that you can enable using the Cleanse element within the match rule configuration. The noise words removal function must be enabled through a comparator and/or match token class. Two of the comparator classes and two of the match token classes offer in-built noise words removal using internal lists of words developed by Reltio. But you can apply a list of your own design by creating a custom comparator and custom match token class and declaring your list with that custom class.

Order of execution

When a cleanser is present in a match rule, it runs before the match token class and before the comparator class. It effectively replaces the attribute's values with a cleansed or transformed set of values that the match token and the comparator class use as input.