To prevent combinations of records when the same contact point is used across several individuals, what should you do?

• A. Include many attributes and contact points
• B. Avoid using match rules with Individual Attributes and contact points, since this is not a recommended practice
• C. Set up match rules with a single connected point
• D. Ensure names are included into the rules

Answer: (D)

When identifying records across a dataset, you want to stop different people from being merged just because they share a contact point. Relying on a single contact point (like an email or phone) can cause several individuals to be treated as one person since that same point appears for multiple people.

Including names in the matching rules adds a distinct signal that helps distinguish individuals who share a contact point. By requiring that both the contact point and the name align (or by using name as a key attribute alongside the contact point), the identity resolution knows when records truly belong to the same person and when they don’t, reducing accidental merges.

In practice, you’d design match rules so that a match is only confirmed when multiple attributes agree, such as contact point plus a name (and potentially other identifiers). This improves accuracy and maintains separate identities when appropriate.

Other options aren’t as effective because focusing on many attributes can complicate matches or create conflicts, avoiding match rules with these attributes undermines the purpose of disambiguation, or using a single point alone isn’t enough to reliably separate individuals. Names provide a practical disambiguator alongside the contact point.