A label is a logical object that provides a different means of representing an attribute . In other words, a label applies additional descriptors to the related attribute.

Each label can be assigned to only one attribute. An attribute can have one or multiple labels. For example, the Department attribute can be represented by different labels, such as Full name, Shortened name, Number. When you choose a label for the Department attribute, you define how you want the attribute values (the company departments) to be displayed:

  • Using the Full name label: Human Resources, Research and Development, Quality Assurance
  • Using the Shortened name label: HR, RD, QA
  • Using the Number label: 1 for Human Resources, 2 for Research and Development, and 3 for Quality Assurance

The following table shows the relationship of attributes, attribute labels, and attribute values:

AttributeAttribute LabelAttribute Values
DepartmentFull nameHuman Resources
Research and Development
Quality Assurance
Short nameHR

When you create an attribute in your logical data model (LDM), it is added with a single label, which has the same name as the attribute itself. This label becomes the primary label for the attribute. Every attribute has at least one label, and you can add more labels to it.

When the attribute with multiple labels is used in an insight , the attribute values belonging to the primary label will be populated into the insight.

Within an LDM, a label belongs to an attribute in a dataset and must define a source column that corresponds to a column from the physical data model (PDM).