Use Cases

Some use cases call for the fields displayed in a dashboard or look to by dynamic, based on user selection of the data granularity, or metrics they wish to see. This can be done using parameters, which insert user-inputed filter values into your LookML, and determine which fields are returned on the front end.

Dynamic Dimensions

Let’s say you have multiple dimensions or dimension group timeframes that represent different date granularities (i.e. day, month, quarter, year, etc.), and you would like users to be able to select which timeframe the data is grouped by on a dashboard. We can define the following parameter, which will be displayed as a filter on your dashboard:

parameter: date_granularity { 
type: string 
allowed_value: { value: "Day" } 
allowed_value: { value: "Month" } 
allowed_value: { value: "Quarter" } 
allowed_value: { value: "Year" } 
}

We will then apply this parameter to a dimension that ties the parameter’s filter values to our different timeframe fields.

dimension: date {
  label_from_parameter: date_granularity
  sql:
    CASE
    WHEN {% parameter date_granularity %} = 'Day' THEN ${created_date}
    WHEN {% parameter date_granularity %} = 'Month' THEN ${created_month}
    WHEN {% parameter date_granularity %} = 'Quarter' THEN ${created_quarter}
    WHEN {% parameter date_granularity %} = 'Year' THEN ${created_year}
    ELSE NULL
  END ;;
 }

The specified timeframe field will now be returned based on whichever parameter value the user selects on the dashboard. Note that we can use label_from_parameter to pass the selected value label to our tile.

Dynamic Measures

A similar approach can be applied to measures. This is especially useful when you have a group of related metrics, that may not want to display individually in the field picker, or that you wish to display dynamically on a look or dashboard, based on user selection.

The following pattern is used to map parameter values to the different metrics that will be available on our dashboard.

parameter: metric_selector {
  type: string
  allowed_value: {
    label: "Total Revenue"
    value: "total revenue"
  }
  allowed_value: {
    label: "First-Time Shopper Revenue"
    value: "total_first_purchase_revenue"
  }
  allowed_value: {
    label: "Returning Shopper Revenue"
    value: "total_returning_shopper_revenue"
  }
 }

measure: metric {
  label_from_parameter: metric_selector
  type: number
  value_format: "$0.0,\"K\""
  sql:
    CASE
      WHEN {% parameter metric_selector %} = 'total_revenue' THEN ${total_revenue}
      WHEN {% parameter metric_selector %} = 'total_first_purchase_revenue' THEN ${total_first_purchase_revenue}
      WHEN {% parameter metric_selector %} = 'total_returning_shopper_revenue' THEN ${total_returning_shopper_revenue}
      ELSE NULL
    END ;;
 }

On the frontend, our dashboard will look like this: