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Exposure properties

Overview​

Exposures are defined in properties.yml files nested under an exposures: key. You may define exposures in YAML files that also define sources or models. Exposure properties are "special properties" in that you can't configure them in the dbt_project.yml file or using config() blocks. Refer to Configs and properties for more info.

You can name these files whatever_you_want.yml, and nest them arbitrarily deeply in subfolders within the models/ directory.

Exposure names must contain only letters, numbers, and underscores (no spaces or special characters). For a short human-friendly name with title casing, spaces, and special characters, use the label property.

models/<filename>.yml
version: 2

exposures:
  - name: <string_with_underscores>
    description: <markdown_string>
    type: {dashboard, notebook, analysis, ml, application}
    url: <string>
    maturity: {high, medium, low}  # Indicates level of confidence or stability in the exposure
    tags: [<string>]
    meta: {<dictionary>}
    owner:
      name: <string>
      email: <string>
    
    depends_on:
      - ref('model')
      - ref('seed')
      - source('name', 'table')
      - metric('metric_name')
      
    label: "Human-Friendly Name for this Exposure!"
    config:
      enabled: true | false

  - name: ... # declare properties of additional exposures

Example​

models/jaffle/exposures.yml
version: 2

exposures:

  - name: weekly_jaffle_metrics
    label: Jaffles by the Week              # optional
    type: dashboard                         # required
    maturity: high                          # optional
    url: https://bi.tool/dashboards/1       # optional
    description: >                          # optional
      Did someone say "exponential growth"?

    depends_on:                             # expected
      - ref('fct_orders')
      - ref('dim_customers')
      - source('gsheets', 'goals')
      - metric('count_orders')

    owner:
      name: Callum McData
      email: data@jaffleshop.com


      
  - name: jaffle_recommender
    maturity: medium
    type: ml
    url: https://jupyter.org/mycoolalg
    description: >
      Deep learning to power personalized "Discover Sandwiches Weekly"
    
    depends_on:
      - ref('fct_orders')
      
    owner:
      name: Data Science Drew
      email: data@jaffleshop.com

      
  - name: jaffle_wrapped
    type: application
    description: Tell users about their favorite jaffles of the year
    depends_on: [ ref('fct_orders') ]
    owner: { email: summer-intern@jaffleshop.com }
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