653666abad
# Description Switches Created Bookings to Billable Bookings in the scope of Projected Bookings. I opted for hard switching (thus removing Projected Created Bookings) altogether to avoid having unused models in production. This aims to set the ground to include, in the future, APIs Billable Bookings. Impact in KPIs: * `int_kpis__agg_daily_created_bookings` now is `int_kpis__agg_daily_billable_bookings`. Aside from the name change, it's reduced to 4 metrics to just one. Schema changes also apply. Impact in Projected KPIs: * `int_kpis_projected__agg_daily_created_bookings` now is `int_kpis_projected__agg_daily_billable_bookings`. Fields are also renamed accordingly. * `int_kpis_projected__agg_monthly_created_bookings` now is `int_kpis_projected__agg_monthly_billable_bookings`. Fields are also renamed accordingly. * Schema file is also updated accordingly. Impact on new model for Growth Score: * `int_created_bookings_growth_score_by_deal` now is `int_billable_bookings_growth_score_by_deal`. Fields are also renamed accordingly. * Schema is also updated accordingly. Note that since the end model `int_billable_bookings_growth_score_by_deal` is not used at the moment in reporting, there's no user-facing impact. Also, the rest of modified models are not used for other purposes. # 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: #29374
436 lines
16 KiB
YAML
436 lines
16 KiB
YAML
version: 2
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models:
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- name: int_kpis_projected__dimension_dates
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description: |
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This model provides the daily time dimensionality needed
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for the projection of KPIs.
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It considers:
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- Dates from the current month, up to the end of it,
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indistinctly if it's in the future or not.
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- Dates from the 3 past complete months.
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This model is intended to be used as a dimension table for
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the projection of KPIs, thus it's expected to be joined with
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the fact table containing the KPIs to be projected.
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columns:
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- name: date
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data_type: date
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description: Specific date. It's the primary key of this model.
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data_tests:
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- unique
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- not_null
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- name: first_day_month
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data_type: date
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description: |
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First day of the month corresponding to the date field.
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data_tests:
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- not_null
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- name: last_day_month
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data_type: date
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description: |
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Last day of the month corresponding to the date field.
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data_tests:
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- not_null
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- name: previous_6_days
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data_type: date
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description: Date of the previous 6 days with respect to the date field.
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data_tests:
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- unique
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- not_null
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- name: is_end_of_month
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data_type: boolean
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description: True if it's end of month, false otherwise.
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data_tests:
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- not_null
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- name: is_current_month
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data_type: boolean
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description: |
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True if the date is within the current month, false otherwise.
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data_tests:
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- not_null
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- name: is_in_the_future
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data_type: boolean
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description: |
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True if the date is in the future, false otherwise. Note that is in the
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future will also include the current day, as we can only consider full-closed
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data up to yesterday.
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data_tests:
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- not_null
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- name: is_latest_historical_date
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data_type: boolean
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description: |
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True if the date is the latest historical date, false otherwise.
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The latest historical date is the latest date from which we have full information.
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This should be yesterday.
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data_tests:
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- not_null
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- name: is_available_for_same_month_projection
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data_type: boolean
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description: |
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True if the date is available for the projection of KPIs for the same month,
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false otherwise. This will be true for all days contained within the first day
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of the month up to yesterday. This will apply for both the current month and
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the 3 months.
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If today is 10th of May, and data is available up to 9th of May, then all days
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from 1st to 9th of May, April, March and February will be available for projection.
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If today is 1st of May, then no dates will be available for projection.
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data_tests:
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- not_null
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- name: is_available_for_last_7_days_projection
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data_type: boolean
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description: |
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True if the date is available for the projection of KPIs for the past 7 days,
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false otherwise. This will be true only for yesterday and the equivalent day for
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the previous 3 months.
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If today is 10th of May, and data is available up to 9th of May, then all days
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only 9th of May, 9th of April, 9th of March and 9th of February will be available
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for projection.
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If today is 1st of May, then 30th of April, 31st of March, 28th of February and
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31st of January will be available for projection.
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data_tests:
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- not_null
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- name: int_kpis_projected__agg_daily_billable_bookings
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description: |
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This model provides the projected daily billable bookings.
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It considers 2 computations:
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- The daily billable bookings for the current month,
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- The daily billable bookings in the past 7 days,
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and the final value is an arithmetic mean of both.
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This model also retrieves the actual billable bookings to be able
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to compare the projected values with the actual ones.
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data_tests:
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- dbt_utils.unique_combination_of_columns:
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combination_of_columns:
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- date
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- dimension
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- dimension_value
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columns:
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- name: date
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data_type: date
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description: |
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The start and end date of the time range considered for the
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metrics in this record.
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data_tests:
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- not_null
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- name: dimension
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data_type: string
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description: The dimension or granularity of the metrics.
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data_tests:
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- assert_dimension_completeness:
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metric_column_names:
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- actual_daily_billable_bookings
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- accepted_values:
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values:
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- global
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- by_number_of_listings
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- by_billing_country
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- by_business_scope
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- by_deal
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- name: dimension_value
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data_type: string
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description: The value or segment available for the selected dimension.
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data_tests:
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- not_null
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- name: first_day_month
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data_type: date
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description: |
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First day of the month corresponding to the date field.
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data_tests:
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- not_null
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- name: last_day_month
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data_type: date
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description: |
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Last day of the month corresponding to the date field.
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data_tests:
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- not_null
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- name: is_end_of_month
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data_type: boolean
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description: True if it's end of month, false otherwise.
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data_tests:
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- not_null
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- name: is_current_month
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data_type: boolean
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description: |
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True if the date is within the current month, false otherwise.
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data_tests:
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- not_null
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- name: is_in_the_future
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data_type: boolean
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description: |
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True if the date is in the future, false otherwise. Note that is in the
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future will also include the current day, as we can only consider full-closed
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data up to yesterday.
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data_tests:
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- not_null
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- name: is_latest_historical_date
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data_type: boolean
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description: |
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True if the date is the latest historical date, false otherwise.
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The latest historical date is the latest date from which we have full information.
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This should be yesterday.
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data_tests:
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- not_null
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- name: daily_billable_bookings_for_reporting_source
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data_type: string
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description: |
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The source of the daily billable bookings for reporting.
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This field is used to identify the source of the data displayed
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in daily_billable_bookings_for_reporting to differentiate between
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the actual and projected values.
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It's aimed for reforting purposes as any historical month will
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contain the actual figures.
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data_tests:
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- not_null
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- accepted_values:
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values:
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- ACTUAL
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- PROJECTED
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- name: daily_billable_bookings_for_reporting
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data_type: integer
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description: |
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The daily billable bookings for reporting purposes.
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This field contains both the actual and projected values.
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Any date in the future will contain projected values, while
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any date in the past will contain actual values.
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data_tests:
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- not_null
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- name: daily_billable_bookings_for_evaluation_source
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data_type: string
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description: |
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Important: This field is used to evaluate the performance
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of the projections!
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The source of the daily billable bookings for evaluation.
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This field is used to identify the source of the data displayed
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in daily_billable_bookings_for_evaluation to differentiate between
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the actual and projected values.
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It's aimed for evaluation purposes as any historical month can
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contain projected figures.
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data_tests:
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- not_null
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- accepted_values:
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values:
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- ACTUAL
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- PROJECTED
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- name: daily_billable_bookings_for_evaluation
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data_type: integer
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description: |
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Important: This field is used to evaluate the performance
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of the projections!
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The daily billable bookings for evaluation purposes.
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This field contains both the actual and projected values.
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Any date in the future will contain projected values. Any date
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in the past which day is after the yesterday day will also contain
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projected values. Any date in the past which day is before the
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yesterday day will contain actual values.
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data_tests:
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- not_null
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- name: projected_daily_billable_bookings
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data_type: integer
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description: |
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The projected daily billable bookings. This field is the result
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of the projection of the daily billable bookings for the current month
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and the past 7 days.
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data_tests:
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- not_null
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- name: actual_daily_billable_bookings
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description: |
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The actual billable bookings for the same period as the projected ones.
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This comes from the standard KPIs.
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data_tests:
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- not_null
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- name: same_month_trend_daily_billable_bookings
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data_type: float
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description: |
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The average daily billable bookings for the current month.
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This field is the result of the division of the actual daily billable
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bookings to date by the number of days available within the current month
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to date, and contains decimals.
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This is just for information purposes.
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data_tests:
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- not_null
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- name: last_7_days_trend_daily_billable_bookings
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data_type: float
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description: |
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The average daily billable bookings for the past 7 days.
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This field is the result of the division of the actual daily billable
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bookings for the past 7 days by 7 days, and contains decimals.
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This is just for information purposes.
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data_tests:
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- not_null
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- name: same_month_trend_total_billable_bookings
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data_type: integer
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description: |
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The total billable bookings for the current month.
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This field is the result of the sum of the actual daily billable
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bookings to date.
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This is just for information purposes.
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- name: last_7_days_trend_total_billable_bookings
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data_type: integer
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description: |
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The total billable bookings for the past 7 days.
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This field is the result of the sum of the actual daily billable
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bookings for the past 7 days.
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This is just for information purposes.
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- name: same_month_trend_total_available_days
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data_type: integer
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description: |
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The total available days for the current month.
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This field is the result of the count of the days available within
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the current month to date.
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This is just for information purposes.
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- name: last_7_days_trend_total_available_days
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data_type: integer
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description: |
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The total available days for the past 7 days.
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This field is the result of the count of the days available for the
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past 7 days.
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This is just for information purposes.
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- name: int_kpis_projected__agg_monthly_billable_bookings
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description: |
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This model provides the projected monthly billable bookings per dimension
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and dimension value. It only considers the current month.
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Historical data is considered only to assess the performance of the
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projections.
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The projection logic is handled on the equivalent daily model,
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please refer to it for more information.
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data_tests:
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- dbt_utils.unique_combination_of_columns:
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combination_of_columns:
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- dimension
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- dimension_value
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columns:
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- name: start_date
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data_type: date
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description: |
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The start date of the time range considered for the metrics in this record.
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data_tests:
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- not_null
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- name: end_date
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data_type: date
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description: |
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The end date of the time range considered for the metrics in this record.
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data_tests:
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- not_null
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- name: dimension
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data_type: string
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description: The dimension or granularity of the metrics.
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data_tests:
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- assert_dimension_completeness:
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metric_column_names:
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- actual_billable_bookings
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- accepted_values:
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values:
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- global
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- by_number_of_listings
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- by_billing_country
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- by_business_scope
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- by_deal
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- name: dimension_value
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data_type: string
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description: The value or segment available for the selected dimension.
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data_tests:
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- not_null
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- name: current_month_projected_billable_bookings
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data_type: integer
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description: |
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The projected monthly billable bookings for the current month.
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This field is the result of the sum of the actual daily billable bookings
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for the current month to date and the projected daily billable bookings
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for the rest of the days in the month that are in the future.
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The closest we are to the end of the month, the more accurate this value will be.
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In order to check how good or bad the projection is, please refer to the
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historical_monthly_mean_absolute_error and
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historical_monthly_mean_absolute_percentage_error fields.
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data_tests:
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- not_null
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- name: actual_billable_bookings
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data_type: integer
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description: |
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The sum of the actual daily billable bookings for the current month to date.
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This comes from the standard KPIs.
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data_tests:
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- not_null
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- name: historical_monthly_mean_absolute_error
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data_type: float
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description: |
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The mean absolute error for this dimension and dimension value.
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This field is used to assess the performance of the projections.
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This is based on the absolute differences between the projected
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monthly billable bookings for each previous month vs the actual value.
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In order to be consistent, it uses the same number of days available
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for the current month to date as the actual value, and the rest of the days
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are projected.
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This computation is applied for the past 3 months, and the value displayed
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here is an average of the absolute differences.
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The closest to 0, the better the projection.
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- name: historical_monthly_mean_absolute_percentage_error
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data_type: float
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description: |
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The mean absolute percentage error for this dimension and dimension value.
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This field is used to assess the performance of the projections.
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This is based on the absolute percentage differences between the projected
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monthly billable bookings for each previous month vs the actual value.
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In order to be consistent, it uses the same number of days available
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for the current month to date as the actual value, and the rest of the days
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are projected.
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This computation is applied for the past 3 months, and the value displayed
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here is an average of the absolute percentage differences.
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The closest to 0, the better the projection.
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