Naming Fields for Readability

[Brett_Sauve]

Dimension and measure names can get confusing, especially as models grow. Making the proper field references while writing LookML, and choosing the correct field in the field picker, requires thoughtful naming. One approach that will help with this is a consistent naming methodology. The following conventions are those often used internally at Looker.

“Count” for Count Measures

type: count measures are called [Filter] Count. For example:

- view: users
  fields:
  - measure: count
    type: count

  - measure: active_count
    type: count
    filters:
      status: 'active'

This will give names in the Looker UI like:

• USERS Count
• USERS Active Count

These field names read naturally, although business users may not initially know to search for “count” as opposed to “number of” or “total”. However, with some very simple training, this seems to be the best option.

We don’t use “number of” or “total” for counts, because we want to reserve those words for other cases.

“Unique Count” for Count Distinct Measures

type: count_distinct measures are called Unique [Filter] [Entity] Count. For example:

- view: users
  fields:
  - measure: unique_user_count
    type: count_distinct
    sql: ${id}

  - measure: unique_active_user_count
    type: count_distinct
    sql: ${id}
    filters:
      status: 'active'

  - measure: unique_name_count
    type: count_distinct
    sql: ${name}

This will give names in the Looker UI like:

• USERS Unique User Count
• USERS Unique Active User Count
• USERS Unique Name Count

“Total” for Sum Measures

type: sum measures are called Total [Filter] [Entity]. For example:

- view: orders
  fields:
  - measure: total_revenue
    type: sum
    sql: ${TABLE}.revenue

  - measure: total_chicago_revenue
    type: sum
    sql: ${TABLE}.revenue
    filters:
      city: 'Chicago'

This will give names in the Looker UI like:

• ORDERS Total Revenue
• ORDERS Total Chicago Revenue

“Number of” for Quantity Dimensions

type: number dimensions that represent a quantity are called Number of [Entity]. For example:

- view: orders
  fields:
  - dimension: number_of_items
    type: number
    sql: ${TABLE}.items

This will give names in the Looker UI like:

• ORDERS Number of Items

Using the word “count” or “total” in this case can be quite confusing, because you will not know if you are working with a dimension or measure.

“Average” for Average Measures

type: average measures are called Avg [Filter] [Entity]. For example:

- view: orders
  fields:
  - measure: avg_revenue
    type: average
    sql: ${TABLE}.revenue

  - measure: avg_chicago_revenue
    type: average
    sql: ${TABLE}.revenue
    filters:
      city: 'Chicago'

This will give names in the Looker UI like:

• ORDERS Avg Revenue
• ORDERS Avg Chicago Revenue

“Over” or “Per” For Ratios

Measures and dimensions that are based on ratios between two other fields are called [Numerator] over [Denominator] or [Numerator] per [Denominator]. For example:

- view: orders
  fields:
  - dimension: revenue_per_number_of_items
    type: number
    sql: ${revenue} / ${number_of_items}

  - measure: total_revenue_per_unique_customer
    type: number
    sql: ${total_revenue} / ${unique_customer_count}

This will give names in the Looker UI like:

• ORDERS Revenue Per Number Of Items
• ORDERS Total Revenue Per Unique Customer

If you were to call the first dimension something like Avg Revenue Per Item it would be less clear that you were using a type: number dimension instead of a type: average measure.