Data unification overview

After setting up the data sources, you can unify the data. Data unification lets you unify once-disparate data sources into a single master dataset that provides a unified view of that data.

For individual consumers (B-to-C) where the data is centered around individuals, unification provides a unified view of your customers. For business accounts (B-to-B) where the data is centered around accounts, unification provides a unified view of your accounts. Contact unification (preview) allows contacts for those accounts to be separately unified and associated with the accounts.

Data can be unified on a single table or multiple tables. Tables were previously called entities.

The unification process maps customer data from your data sources, removes duplicates, matches the data across tables, and creates a unified profile. Unification is performed in the following order:

  1. Source fields (previously called Map): In the source fields step, select tables and fields to include in the unify process. Map fields to a common semantic type that describes the purpose of the field.

  2. Duplicate records (previously part of Match): In the duplicate records step, optionally define rules to remove duplicate customer records from within each table.

  3. Matching conditions (previously called Match): In the matching conditions step, define rules that match customer records between tables. When a customer is found in two or more tables, a single consolidated record is created with all columns and data from each table.

  4. Unified customer fields (previously called Merge): In the unified customer fields step, determine which source fields should be included, excluded, or merged into a unified customer profile.

  5. Review and create the unified profile.

After completing data unification, you can optionally: