Simple metrics

Simple metrics are metrics that directly reference a single measure, without any additional measures involved. They are aggregations over a column in your data platform and can be filtered by one or multiple dimensions.

The parameters, description, and type for simple metrics are:

tip

Note that we use dot notation (.) to indicate whether a parameter is nested within another parameter. For example, measure.name means the name parameter is nested under measure.

Parameter	Description	Required	Type
name	The name of the metric.	Required	String
description	The description of the metric.	Optional	String
type	The type of the metric (cumulative, derived, ratio, or simple).	Required	String
label	Defines the display value in downstream tools. Accepts plain text, spaces, and quotes (such as orders_total or "orders_total").	Required	String
type_params	The type parameters of the metric.	Required	Dict
measure	A list of measure inputs.	Required	List
measure.name	The measure you're referencing.	Required	String
measure.alias	Optional alias to rename the measure.	Optional	String
measure.filter	Optional filter applied to the measure.	Optional	String
measure.fill_nulls_with	Set the value in your metric definition instead of null (such as zero).	Optional	Integer
measure.join_to_timespine	Indicates if the aggregated measure should be joined to the time spine table to fill in missing dates. Default false.	Optional	Boolean

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The following displays the complete specification for simple metrics, along with an example.

metrics:
  - name: The metric name # Required
    description: the metric description # Optional
    type: simple # Required
    label: The value that will be displayed in downstream tools # Required
    type_params: # Required
      measure: 
        name: The name of your measure # Required
        alias: The alias applied to the measure. # Optional
        filter: The filter applied to the measure. # Optional
        fill_nulls_with: Set value instead of null  (such as zero) # Optional
        join_to_timespine: true/false # Boolean that indicates if the aggregated measure should be joined to the time spine table to fill in missing dates. # Optional

For advanced data modeling, you can use fill_nulls_with and join_to_timespine to set null metric values to zero, ensuring numeric values for every data row.

Simple metrics example

  metrics: 
    - name: customers
      description: Count of customers
      type: simple # Pointers to a measure you created in a semantic model
      label: Count of customers
      type_params:
        measure: 
          name: customers # The measure you are creating a proxy of.
          fill_nulls_with: 0 
          join_to_timespine: true
          alias: customer_count
          filter: {{ Dimension('customer__customer_total') }} >= 20
    - name: large_orders
      description: "Order with order values over 20."
      type: simple
      label: Large orders
      type_params:
        measure: 
          name: orders
      filter: | # For any metric you can optionally include a filter on dimension values
        {{Dimension('customer__order_total_dim')}} >= 20

Related docs

• Fill null values for simple, derived, or ratio metrics

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