Removed changes for cutoff date
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4 changed files with 14 additions and 37 deletions
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@ -1,6 +1,10 @@
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with
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int_monthly_aggregated_metrics_history_by_deal as (
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select * from {{ ref("int_monthly_aggregated_metrics_history_by_deal") }}
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select
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*,
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(date_trunc('month', date) + interval '2 month' - interval '1 day')::date
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as next_month_end_date
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from {{ ref("int_monthly_aggregated_metrics_history_by_deal") }}
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),
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int_kpis__dimension_deals as (select * from {{ ref("int_kpis__dimension_deals") }}),
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deal_attributes as (
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@ -20,7 +24,7 @@ with
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)
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-- Calculate expected MRR per deal by each dimension
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select
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(date_trunc('month', m.date) + interval '2 month' - interval '1 day')::date as date,
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m.next_month_end_date as date,
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'by_number_of_listings' as dimension,
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d.hubspot_listing_segmentation as dimension_value,
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sum(coalesce(m.total_revenue_in_gbp, 0)) / count(*) as expected_mrr_per_deal
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@ -36,7 +40,7 @@ where d.hubspot_listing_segmentation <> 'UNSET'
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group by 1, 2, 3
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union all
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select
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(date_trunc('month', m.date) + interval '2 month' - interval '1 day')::date as date,
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m.next_month_end_date as date,
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'by_billing_country' as dimension,
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d.main_billing_country_iso_3_per_deal as dimension_value,
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sum(coalesce(m.total_revenue_in_gbp, 0)) / count(*) as expected_mrr_per_deal
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@ -52,7 +56,7 @@ where d.hubspot_listing_segmentation <> 'UNSET'
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group by 1, 2, 3
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union all
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select
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(date_trunc('month', m.date) + interval '2 month' - interval '1 day')::date as date,
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m.next_month_end_date as date,
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'global' as dimension,
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'global' as dimension_value,
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sum(coalesce(m.total_revenue_in_gbp, 0)) / count(*) as expected_mrr_per_deal
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@ -1712,8 +1712,11 @@ models:
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"This table provides data on the Onboarding Monthly Recurring Revenue (MRR).
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The Onboarding MRR is an estimate of the expected monthly revenue generated by
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each new deal. It is calculated by taking the total revenue generated by all
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active accounts over the last 12 previous months and dividing it by the number
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of active months for each account."
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active accounts over the last 12 previous months (before the ongoing month)
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and dividing it by the number of active months for each account during this
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period.
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For example in December 2023 we will calculate the Onboarding MRR for a deal
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using the revenue from December 2022 to November 2023."
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data_tests:
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- dbt_utils.unique_combination_of_columns:
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@ -70,7 +70,7 @@ where
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or lower(metric) like '%retained%'
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or lower(metric) like '%damage host%'
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)
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and {{ is_date_before_previous_month_fixed_20("date") }}
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and {{ is_date_before_previous_month("date") }}
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)
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-- Not show current month if the metric is Expected MRR, unlike other
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-- revenue metrics, Expected MRR is calculated for the next month, so it is not
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