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What are Identifiers?

Identifiers represent real-world concepts within a business context, like customers, transactions, or ad campaigns. Analyses often revolve around specific identifiers such as customer churn or annual recurring revenue modeling. These identifiers are depicted in semantic models using id columns, acting as join keys linking other semantic models in the semantic graph.

Identifiers offer a clear structure to the underlying data, enabling more coherent and insightful analysis.

How to Define Identifiers

Every identifier requires a name and type. The name can reference the key column name from the data table, or function as an alias with the column name referenced in the expr parameter.

How to create and edit an identifier

In the Catalog section click click on a table you want to set up an identifier for. Then click on the Entities tab.

Specification for Identifiers

Identifiers are illustrated using these parameters:

  - name: [name]
    type: [Primary or Natural or Foreign or Unique]
    description: [description of the field or role]
    expr: [column name or expression, defaults to the name if not provided]

For instance, in a semantic model detailing sales, identifiers can be defined as:

  - name: transaction
    type: primary
    expr: id_transaction
  - name: order
    type: foreign
    expr: id_order
  - name: user
    type: foreign
    expr: substring(id_order from 2)

Identifier Types and Join Logic

We leverage different join logics based on the identifier type:

This identifier type signifies that each row in the table has only one unique record, encompassing all records in the data platform.

Identifiers (or join keys) in a semantic model are identified by their name. They need to be unique within a model, but not across different models.

Utilizing Identifiers as Dimensions

Identifiers can also function as dimensions, permitting the aggregation of a metric to the identifier’s granularity.

Wrapping up

Identifiers are foundational, establishing relationships and ensuring seamless data analysis. Through a keen understanding of identifiers and their applications, businesses can derive richer insights and make data-driven decisions.