Netskope has renamed Data Identifier to Entity. If you see “Data Identifier” in older screenshots or support articles, it refers to the same feature now called “Entity.”
A DLP Entity (formerly called a Data Identifier) is one building block DLP rules use to detect sensitive data in content. An Entity tells a rule what to look for, a Social Security number, a credit card number, a person’s name, a genomic sequence identifier, or any other pattern your organization cares about.
A DLP rule is built from one or more Entities. Entities come in three forms.
| Entity Type | What It Detects | Who Defines It |
|---|---|---|
| Predefined Entity | Common regulatory and sensitive data patterns, such as SSNs, payment cards, and national IDs | Netskope |
| Custom Entity | Organization-specific patterns, such as internal ID formats, project codenames, or proprietary record numbers | You |
| Predefined AI Entity (NER) | Contextual, unstructured data that requires language understanding rather than pattern matching, such as person names, PII in prose, or genomic identifiers | Netskope, using Named Entity Recognition (NER) |
To access Entities, go to Policies > Profiles > DLP > DLP Rules > Entities.
Choosing the Right Entity Type
Use the following table to decide which Entity type fits your use case.
| Your Data Looks Like | Use |
|---|---|
| A fixed-format regulated identifier Netskope already supports | Predefined Entity |
| A fixed-format pattern unique to your organization | Custom Entity (regex or keyword) |
| A list of known terms, codenames, or phrases | Custom Dictionary (keyword or regex) |
| Free-text personal data, such as names or addresses | Predefined AI Entity, PII domain |
| Free-text genomic or human-omic data | Predefined AI Entity, Genomic or Human-omic domain |
For predefined identifiers, including the newer AI-based (NER) identifiers, see Select Predefined Entities. For organization-specific patterns, see Select Custom Entities.
To learn more: DLP Entity.