Reltio Connect

Name Cleansers in Reltio: An Overview

Today, Gino Fortunato will guide us through the role of name cleansers for data matching in Reltio. Our agenda encompasses an understanding of name cleansers, their significance, and configuration nuances. Gino will discuss three types of cleansers in Reltio—name cleanser, string replacement, and noise removal—with a focus on the name cleanser and its role in the matching process.

Understanding Name Cleansers

Name cleansers serve a vital role in detecting matching names in Reltio's matching framework. Key functionalities include:

1. Name cleansers operate exclusively within the matching framework without altering the actual data.
2. The cleansers function silently in the background, invisible in the user interface (UI).
3. Unlike email and phone cleansers that visibly alter data, the name cleanser works discreetly.
4. Reltio offers a standalone name cleanser, activated through cleanse elements in the natural language configuration.

Configuring Name Cleansers

We will now explore how to configure name cleansers within Reltio's matching rules:

1. The default 2012 name cleanser is easily activated.
2. The cleanser configuration involves uploading a file called the name dictionary cleanser.
3. Reltio provides comprehensive documentation, including a file containing mappings for common names like Bob and Robert.
4. You are encouraged to review this file to ensure its mappings align with your specific needs.

Customizing Name Cleansers

Reltio offers customizable name cleansers to cater to diverse use cases:

1. The provided name dictionary cleansers mainly cover Western names and English nicknames.
2. For synonym lists catering to non-English names, custom files can be created and uploaded.
3. Reltio supports adding custom name dictionaries, giving administrators the flexibility to expand the mappings.
4. However, custom files involve a support process and are uploaded behind the Reltio firewall.

Integrating Name Cleansing with Reference Data Management (RDM)

Reltio integrates with RDM for more advanced and dynamic name cleansing:

1. Define the equivalency mappings for names by creating a lookup in RDM.
2. Configure lookup values, ensuring the canonical value codes are lowercase.
3. Specify the RDM tenant ID, service URI, and lookup type in the RDM cleanser configuration within the matching rule.
4. Use the appropriate authentication server for authorization.

Understanding the Cumulative Effect of Match Cleansers

Understanding the cumulative effect of match cleansers within the matching rules is crucial:

1. Match cleansers cumulatively operate on a field, affecting all matching rules containing cleansers for that field.
2. The cumulative effect arises from the union of cleansed values generated by the match cleansers.
3. Although the cumulative effect may seem counterintuitive initially, it has proven to be effective in real-world scenarios.

Name cleansers represent a vital cog in Reltio's matching framework, enabling precise identification of matching names. Whether administrators use default cleansers or opt for customization through RDM, the outcome invariably enhances data quality and matching results. Appreciating the configuration and cumulative impacts of match cleansers is integral to successful implementation.

We are grateful for Gino Fortunato's expert insights into the power of name cleansers in Reltio. We hope this discussion proved enlightening and eagerly anticipate your participation in our upcoming events!

For questions, check out the Reltio Community and ask your questions there https://community.reltio.com/home