Fundamental Concepts Related to Matching

Learn about the concept of matching in the Reltio Connected Data Platform.

This article provides an overview of the fundamental concepts related to matching in the Reltio Connected Data Platform

Purpose of matching

The matching functionality compares and merges duplicate records to ensure data validity.

How matching work

Matching in the Reltio Connected Data platform operates continuously and in real-time. When a user creates or updates a record in the tenant, the platform cleanses and processes the record to find matches within the existing set of records. This is the platform’s default behavior; cleansing and processing can also be done as a batch job. (See Tenant-Level Match Strategy

Relationship of survivorship to merging

Survivorship and merging are independent processes in the Reltio platform. Learn more about survivorship here.

Role of entity types and rules in matching

Each entity type (e.g., contact, organization, product) has its own set of match groups. Each match group holds a single rule along with other properties that dictate the behavior of the rule within that group. Comparison Operators (e.g., Exact, ExactOrNull, and Fuzzy) and attributes comprise a single rule.

Reltio provides a set of match groups, based on best practices, with each of its out-of-the-box(OOTB) solution accelerators. You can remove, change or supplement these groups as needed using Reltio’s Match Rule Editor. Learn more about this powerful tool.

Use of match tokens and comparators within a match group

Reltio uses match tokens to help the match engine quickly find candidate match values. The comparison formula within a match rule is used to adjudicate a candidate match pair and will evaluate to true or false (or a score if matching is based on relevance).

Three potential outcomes of matching

Reltio’s matching function will do one of three things with a pair of records:
  1. Nothing (if the comparison formula determines that there is no match)
  2. Issue a directive to merge the pair
  3. Issue a directive to queue the pair for review by a data steward

Available cleansers to use for matching

Using the Reltio platform, you can configure cleansers such as address, email, phone and others within your tenant. You can also use Reltio’s OOTB set of match-level cleansers, which are used exclusively by the match engine.

Matching internal and external record

The match rules you develop can be used to match and merge records within a tenant. You can also match records from an external file against records within your tenant using the External Match API, by using the External Match Application within the Reltio Console. The Scope parameter controls Internal vs External matching. Learn more about how to select external entities for matching.

Reltio writes the results of internal-to-external matching jobs to an output file in CSV format for your review.

How match rules for your tenant are related to Data Tenant Subscription Service (DTSS)

Reltio DTSS does not use the match rules you develop for your tenant to match Data Tenant records to your tenant records. DTSS uses rules that are held in the Data Tenant’s configuration. If your tenant subscribes to a Reltio Data Tenant, your DTSS subscription may modify the behavior of the Data Tenant’s match rules but not significantly.