Addressed comments
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3 changed files with 12 additions and 5 deletions
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@ -1,5 +1,3 @@
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{% set starting_date = "('2020-01-01')" %}
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with
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unique_dimensions as (
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select distinct has_payment, has_id_check
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@ -8,4 +6,4 @@ with
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select d.date_day, ud.has_payment, ud.has_id_check
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from {{ ref("int_dates") }} as d
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cross join unique_dimensions as ud
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where d.date_day >= {{ starting_date }}
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where d.date_day >= {{ var("start_date") }}
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@ -72,6 +72,7 @@ with
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select
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gk.date_day,
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gk_py.date_day as py_date_day,
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gk.has_payment,
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gk.has_id_check,
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sum(
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@ -130,4 +131,4 @@ left join
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and gk.has_id_check = gk_py.has_id_check
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-- Here we use a group by because of leap days that generate duplicity when being
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-- moved to another year
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group by gk.date_day, gk.has_payment, gk.has_id_check
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group by gk.date_day, gk_py.date_day, gk.has_payment, gk.has_id_check
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@ -5829,7 +5829,8 @@ models:
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The unique key corresponds to the deepest granularity of the model,
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in this case:
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- date_day,
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- date_day,
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- py_date_day,
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- id_deal,
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- has_id_check.
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@ -5837,6 +5838,7 @@ models:
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- dbt_utils.unique_combination_of_columns:
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combination_of_columns:
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- date_day
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- py_date_day
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- has_payment
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- has_id_check
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columns:
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@ -5846,6 +5848,12 @@ models:
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tests:
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- not_null
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- name: py_date_day
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data_type: date
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description: |
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Date on the previous year of when Guest Journeys have been completed.
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Note that this date can be NULL for leap days (29th February)
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- name: has_payment
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data_type: string
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description: Has there been any guest payments on the guest journey.
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