Exposures

▶Changelog

Related documentation

• Exposure properties
• exposure: selection method

Getting started

Exposures make it possible to define and describe a downstream use of your dbt project, such as in a dashboard, application, or data science pipeline. By defining exposures, you can then:

• run, test, and list resources that feed into your exposure
• populate a dedicated page in the auto-generated documentation site with context relevant to data consumers

Declaring an exposure

Exposures are defined in .yml files in your models directory (as defined by the source-paths config), nested under an exposures: key.

models/<filename>.yml

exposures:
  
  - name: weekly_jaffle_metrics
    type: dashboard
    maturity: high
    url: https://bi.tool/dashboards/1
    description: >
      Did someone say "exponential growth"?
    
    depends_on:
      - ref('fct_orders')
      - ref('dim_customers')
      - source('gsheets', 'goals')
      
    owner:
      name: Claire from Data
      email: data@jaffleshop.com

Available properties

Required:

• name (must be unique among exposures)
• type: one of dashboard, notebook, analysis, ml, application (used to organize in docs site)
• owner: email

Expected:

• depends_on: list of refable nodes (ref + source)

Optional:

• url
• maturity: one of high, medium, low
• owner: name

We plan to add more subtypes and optional properties in future releases.

Referencing exposures

Once an exposure is defined, you can run commands that reference it:

dbt run -m +exposure:weekly_jaffle_metrics
dbt test -m +exposure:weekly_jaffle_metrics

When we generate our documentation site, you'll see the exposure appear:

Dedicated page in dbt-docs for each exposure

Exposures appear as orange-y nodes in the DAG

Exposures are new!

Exposures were introduced in dbt v0.18.1, with a limited set of supported types and properties. If you're interested in requesting or contributing additional properties, check out issue dbt#2835.