9f7f92912f
# Description Creates a new metric: Confident Stay Revenue. This includes: * Setting the computation in `int_mtd_vs_previous_year_metrics` * Configuring the metric behavior in `int_mtd_aggregated_metrics`. It follows the same as CIH. * Adding the metric in the completion test. I didn't add it in the outlier test in purpose as any new value would trigger the outlier since there's no history to compare against. Few notes: * I confirm it displays no value, as the product has not been launched. * Note that the inclusion of Confident Stay in Guest Revenue was already handled in the previous PR. Next steps to complete the ticket: * Add in the Data Glossary of Main KPIs the definition of Confident Stay Revenue * Add in the Data Glossary of Account Performance the definition of Confident Stay Revenue # 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. - [N/A] I have checked for DRY opportunities with other models and docs. - [N/A] 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: #30278
103 lines
3.5 KiB
SQL
103 lines
3.5 KiB
SQL
/*
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This test is applied in the reporting layer for Main KPIs,
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specifically on reporting.mtd_aggregated_metrics.
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It just ensures that for the last available date, the sum of metrics
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for any dimension provides an equal or lower aggregated value compared
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to what is expected at Global level, up to a certain threshold.
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This is because some dimensions depend on Deal, and not all users
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have a Deal, thus it's normal that the aggregation might not match the
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Global value on a given metric.
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However, the aggregation cannot be higher, with a certain tolerance,
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than the value reported in the Global dimension.
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*/
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{% set tolerance_threshold = 0.000001 %}
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{% set additive_metric_names = (
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"Bookings Churn Rate",
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"Cancelled Check Out Bookings",
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"Cancelled Created Bookings",
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"Check-In Hero Revenue",
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"Check Out Bookings (Excl. Cancelled)",
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"Churning Deals",
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"Churning Listings",
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"Confident Stay Revenue",
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"Created Bookings (Excl. Cancelled)",
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"Damage Waiver Payouts",
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"Deals Booked in 12 Months",
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"Deals Booked in 6 Months",
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"Deals Booked in Month",
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"Deposit Fees Revenue",
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"Billable Bookings",
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"First Time Booked Deals",
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"First Time Booked Listings",
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"Guest Journey Completed",
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"Guest Journey Created",
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"Guest Journey Started",
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"Guest Journey with Payment",
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"Guest Revenue",
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"Host Resolutions Payouts",
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"Host Resolutions Payment Count",
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"Invoiced APIs Revenue",
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"Invoiced Athena Revenue",
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"Invoiced Old Dashboard Booking Fees Revenue",
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"Invoiced Total Booking Fees Revenue",
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"Invoiced E-Deposit Revenue",
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"Invoiced Listing Fees Revenue",
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"Invoiced Operator Revenue",
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"Invoiced Verification Fees Revenue",
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"Listings Booked in 12 Months",
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"Listings Booked in 6 Months",
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"Listings Booked in Month",
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"New Deals",
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"New Listings",
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"Revenue Churn Rate",
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"Revenue Retained",
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"Revenue Retained Post-Resolutions",
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"Total Check Out Bookings",
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"Total Created Bookings",
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"Total Revenue",
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"Waiver Revenue",
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"Waiver Retained",
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) %}
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with
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dimensions_total_metric_values as (
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select date, dimension, metric, number_format, sum(value) as total_metric_value
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from {{ ref("mtd_aggregated_metrics") }}
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where
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date in (select max(date) from {{ ref("mtd_aggregated_metrics") }})
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and metric in {{ additive_metric_names }}
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group by date, dimension, metric, number_format
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),
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global_dimension_metric_values as (
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select date, dimension, metric, number_format, total_metric_value
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from dimensions_total_metric_values
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where dimension = 'Global'
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),
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other_dimension_metric_values as (
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select date, dimension, metric, number_format, total_metric_value
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from dimensions_total_metric_values
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where dimension != 'Global'
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),
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difference_computation as (
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select
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g.date,
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g.metric,
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o.dimension,
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g.number_format,
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abs(g.total_metric_value) as global_metric_value,
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abs(o.total_metric_value) as dimension_metric_value,
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abs(o.total_metric_value) - abs(g.total_metric_value) as abs_diff,
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abs(o.total_metric_value) / nullif(abs(g.total_metric_value), 0)
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- 1 as rel_diff
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from global_dimension_metric_values as g
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left join
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other_dimension_metric_values as o
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on g.date = o.date
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and g.metric = o.metric
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)
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select *
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from difference_computation
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where abs_diff > {{ tolerance_threshold }}
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