9ba0edb82d
# Description New model: * int_kpis__agg_dates_main_kpis - Serves as the skeleton of dates and dimensions for Main KPIs. It's aggregated since it follows a similar aggregation strategy. It's a single model to feed both Main KPIs visualisations. Note boolean fields are real booleans (true/false) while before these were integers (1/0). This also affects downstream models. Main KPIs flow adaptations to new skeleton model: * int_monthly_aggregated_metrics_history_by_deal * int_monthly_churn_metrics - additionally, calls usual KPIs macro instead of old one * int_mtd_vs_previous_year_metrics Reporting changes to ensure report is not down: * mtd_aggregated_metrics - adaptations on booleans (true-1, false-0) Cleaning: * get_kpi_dimensions macro is no longer used * int_dates_by_deal model and schema entry * int_dates_mtd_by_dimension model and schema entry * int_dates_mtd model and schema entry # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [X] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23763
93 lines
3.7 KiB
SQL
93 lines
3.7 KiB
SQL
{% set dimensions = get_kpi_dimensions_per_model("CHURN_RATES") %}
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{% set churn_lifecycle_states = "('05-Churning')" %}
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{{ config(materialized="table", unique_key=["date", "dimension", "dimension_value"]) }}
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with
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int_monthly_12m_window_contribution_by_deal as (
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select * from {{ ref("int_monthly_12m_window_contribution_by_deal") }}
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),
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int_kpis__agg_dates_main_kpis as (
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select *
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from {{ ref("int_kpis__agg_dates_main_kpis") }}
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where
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dimension in ('global', 'by_number_of_listings', 'by_billing_country')
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and dimension_value <> 'UNSET'
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),
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int_kpis__dimension_daily_accommodation as (
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select * from {{ ref("int_kpis__dimension_daily_accommodation") }}
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),
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int_core__deal as (select * from {{ ref("int_core__deal") }}),
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churn_metrics_per_date as (
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{% for dimension in dimensions %}
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select
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m12wc.date,
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{{ dimension.dimension }} as dimension,
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{{ dimension.dimension_value }} as dimension_value,
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sum(
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case
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when m12wc.deal_lifecycle_state in {{ churn_lifecycle_states }}
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then m12wc.total_revenue_12m_average_contribution
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else 0
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end
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) as total_revenue_churn_average_contribution,
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sum(
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case
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when m12wc.deal_lifecycle_state in {{ churn_lifecycle_states }}
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then m12wc.created_bookings_12m_average_contribution
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else 0
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end
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) as created_bookings_churn_average_contribution,
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sum(
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case
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when m12wc.deal_lifecycle_state in {{ churn_lifecycle_states }}
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then m12wc.listings_booked_in_month_12m_average_contribution
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else 0
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end
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) as listings_booked_in_month_churn_average_contribution
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from int_monthly_12m_window_contribution_by_deal m12wc
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{% if dimension.dimension == "'by_number_of_listings'" %}
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inner join
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int_kpis__dimension_daily_accommodation dda
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on m12wc.id_deal = dda.id_deal
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and m12wc.date = dda.date
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{% elif dimension.dimension == "'by_billing_country'" %}
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inner join
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int_core__deal ud
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on m12wc.id_deal = ud.id_deal
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and ud.main_billing_country_iso_3_per_deal is not null
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{% endif %}
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where deal_lifecycle_state is not null
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group by 1, 2, 3
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{% if not loop.last %}
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union all
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{% endif %}
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{% endfor %}
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)
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-- Final aggregation of subqueries --
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select
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d.year,
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d.month,
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d.day,
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d.date,
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d.dimension,
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d.dimension_value,
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d.is_end_of_month,
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d.is_current_month,
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cast(
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c.total_revenue_churn_average_contribution as numeric(19, 6)
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) as total_revenue_churn_average_contribution,
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cast(
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c.created_bookings_churn_average_contribution as numeric(19, 6)
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) as created_bookings_churn_average_contribution,
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cast(
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c.listings_booked_in_month_churn_average_contribution as numeric(19, 6)
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) as listings_booked_in_month_churn_average_contribution
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from int_kpis__agg_dates_main_kpis d
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left join
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churn_metrics_per_date c
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on c.date = d.date
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and c.dimension = d.dimension
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and c.dimension_value = d.dimension_value
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-- Remove current month dates since data won't be available anyway. This is specific
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-- for this churn metrics model
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where d.is_current_month = false
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