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data-dwh-dbt-project/models/intermediate/kpis/schema.yml
Oriol Roqué Paniagua be0b8c41b6 Merged PR 4411: Propagates New Dash/Old Dash/APIs split in KPIs as per Business Scope 
# Description

Changes:
* Adapt business_kpis_configuration to include By Business Scope as production dimension.
* Sets in int_mtd_metrics_vs_previous_year the selection of business scope dimension for all KPIs models. This does not affect cross kpis models (churn/mrr). I might need to check later how to adapt Churn to include this dimension, but it's not considered as for this PR. Lastly, Billable Bookings excludes New Dash.
* Adapts condition in int_mtd_metrics_vs_previous_year so MTD values would appear independently of these appearing in the previous year. This is, the model was considering that to show current month MTD values, the dimension needed to exist the year prior. This does not happen with New Dash and I assume we never noticed because in any case, most of our dimensions have quite a long history.
* Adapts int_kpis__agg_dates_main_kpis to include the business scope dimension. By the way it's actually handled, it kind of assumes that a Deal can only be in New or Old Dash (this is correct), but while on New Dash, this deal won't have data for Old Dash (this might not be 100% correct). In any case, the global figure should be ok, and only on the deal + business scope dimensionality this could cause some potential problems. However, this is not being reported anyway at the moment.
* Adapts int_kpis__agg_dates_main_kpis to have a proper variable value for the dimensions, and this is further included in business_kpis_configuration as any other model.

Small changes:
* Adapts Churn metrics to read from dimension_deals rather than core__deals. This should be more accurate anyway.

# Checklist

- [ ] The edited models and dependants run properly with production data.
- [ ] The edited models are sufficiently documented.
- [ ] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.

# Other

- [ ] Check if a full-refresh is required after this PR is merged.

Propagates New Dash/Old Dash/APIs split in KPIs as per Business Scope

Related work items: #27356
2025-02-14 14:12:39 +00:00

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version: 2
models:
- name: int_kpis__dimension_dates
description: |
This model provides the daily time dimensionality needed for KPIs.
It only considers dates up-to-yesterday.
columns:
- name: date
data_type: date
description: Specific date. It's the primary key of this model.
data_tests:
- unique
- not_null
- name: year
data_type: int
description: Year number of the given date.
data_tests:
- not_null
- name: month
data_type: int
description: Month number of the given date.
data_tests:
- not_null
- name: week
data_type: int
description: Week number of the given date.
data_tests:
- not_null
- name: day
data_type: int
description: Day monthly number of the given date.
data_tests:
- not_null
- name: first_day_month
data_type: date
description: |
First day of the month corresponding to the date field.
data_tests:
- not_null
- name: last_day_month
data_type: date
description: |
Last day of the month corresponding to the date field.
data_tests:
- not_null
- name: is_end_of_month
data_type: boolean
description: True if it's end of month, false otherwise.
data_tests:
- not_null
- name: is_current_month
data_type: boolean
description: |
True if the date is within the current month, false otherwise.
data_tests:
- not_null
- name: is_month_to_date
data_type: boolean
description: |
True if the date is within the scope of month-to-date, false otherwise.
The scope of month-to-date takes into account both 1) a date being in
the current month or 2) a date corresponding to the same month of the
previous year, which day number cannot be higher than yesterday's day
number.
data_tests:
- not_null
- name: first_day_week
data_type: date
description: |
First day of the week corresponding to the date field.
data_tests:
- not_null
- name: last_day_week
data_type: date
description: |
Last day of the week corresponding to the date field.
data_tests:
- not_null
- name: is_end_of_week
data_type: boolean
description: True if it's end of week, false otherwise.
data_tests:
- not_null
- name: is_current_week
data_type: boolean
description: |
True if the date is within the current week, false otherwise.
data_tests:
- not_null
- name: is_yesterday
data_type: boolean
description: |
True if the date is yesterday, false otherwise.
data_tests:
- not_null
- name: int_kpis__agg_dates_main_kpis
description: |
This model provides the skeleton of dates and dimensions needed for Main KPIs display.
It encapsulates the multiple manners to present data in the reporting, namely, Monthly+MTD
per a given dimension or specifically Monthly by Deal.
The rest of the metrics computed are attached to this master table.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- dimension
- dimension_value
columns:
- name: date
data_type: date
description: |
The end date of the time range considered for the metrics that will be
available in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: year
data_type: int
description: Year number of the given date.
data_tests:
- not_null
- name: month
data_type: int
description: Month number of the given date.
data_tests:
- not_null
- name: day
data_type: int
description: Day monthly number of the given date.
data_tests:
- not_null
- name: first_day_month
data_type: date
description: |
First day of the month corresponding to the date field.
data_tests:
- not_null
- name: last_day_month
data_type: date
description: |
Last day of the month corresponding to the date field.
data_tests:
- not_null
- name: is_end_of_month
data_type: boolean
description: True if it's end of month, false otherwise.
data_tests:
- not_null
- name: is_current_month
data_type: boolean
description: |
True if the date is within the current month, false otherwise.
data_tests:
- not_null
- name: is_end_of_month_or_yesterday
data_type: boolean
description: |
True if the date is the end of the month OR yesterday, false otherwise.
data_tests:
- not_null
- name: int_kpis__lifecycle_daily_accommodation
description: |
This model computes the daily lifecycle segment for each accommodation, also known as
listings.
The information regarding the booking-related time allows for the current status of any listing
regarding its activity. This information is encapsulated in the following columns:
accommodation_lifecycle_state: contains one of the following states
- 01-New: Listings that have been created in the current month, without bookings
- 02-Never Booked: Listings that have been created before the current month, without bookings.
- 03-First Time Booked: Listings that have been booked for the first time in the current month.
- 04-Active: Listings that have booking activity in the past 12 months (that are not FTB nor reactivated)
- 05-Churning: Listings that are becoming inactive because of lack of bookings in the past 12 months
- 06-Inactive: Listings that have not had a booking for more than 12 months.
- 07-Reactivated: Listings that have had a booking in the current month that were inactive or churning before.
- Finally, if none of the logic applies, which should not happen, null will be set and a dbt alert will raise.
Since the states of Active, First Time Booked and Reactivated indicate certain booking activity and are
mutually exclusive, the model also provides information of the recency of the bookings by the following
booleans:
- has_been_booked_within_current_month: If a listing has had a booking created in the current month
- has_been_booked_within_last_6_months: If a listing has had a booking created in the past 6 months
- has_been_booked_within_last_12_months: If a listing has had a booking created in the past 12 months
Note that if a listing has had a booking created in a given month, all 3 columns will be true. Similarly,
if the last booking created to a listing was 5 months ago, only the column has_been_booked_in_1_month
will be false; while the other 2 will be true.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_accommodation
columns:
- name: date
data_type: date
description: Date in which a Listing has a given lifecycle state.
data_tests:
- not_null
- name: id_accommodation
data_type: bigint
description: Id of the accommodation or listing.
data_tests:
- not_null
- name: creation_date_utc
data_type: date
description: Date of when the listing was created.
- name: first_time_booked_date_utc
data_type: date
description: |
Date of the first booking created for a given listing. Can be null if the listing
has never had a booking associated with it.
- name: last_time_booked_date_utc
data_type: date
description: |
Date of the last booking created for a given listing. Can be null if the listing
has never had a booking associated with it. Can be the same as first_time_booked_date_utc
if the listing only had 1 booking in its history.
- name: second_to_last_time_booked_date_utc
data_type: date
description: |
Date of the second-to-last booking created for a given listing, meaning the creation
date of the booking that precedes the last one. It's relevant for the reactivation computation
on the lifecycle. Can be null if the listing has never had a booking associated with it or if
the listing only had 1 booking in its history.
- name: accommodation_lifecycle_state
data_type: character varying
description: |
Contains the lifecycle state of a Listing. The accepted values are:
01-New, 02-Never Booked, 03-First Time Booked, 04-Active, 05-Churning, 06-Inactive,
07-Reactivated. Failing to implement the logic will result in alert.
data_tests:
- not_null
- accepted_values:
values:
- 01-New
- 02-Never Booked
- 03-First Time Booked
- 04-Active
- 05-Churning
- 06-Inactive
- 07-Reactivated
- name: has_been_booked_within_current_month
data_type: boolean
description: If the listing has had a booking created in the current month.
- name: has_been_booked_within_last_6_months
data_type: boolean
description: If the listing has had a booking created in the past 6 months.
- name: has_been_booked_within_last_12_months
data_type: boolean
description: If the listing has had a booking created in the past 12 months.
- name: int_kpis__lifecycle_daily_deal
description: |
This model computes the daily lifecycle of accounts, at deal level.
The information regarding the booking-related time allows for the current status of any
deal regarding its activity. This information is encapsulated in the following columns:
deal_lifecycle_state: contains one of the following states
- 01-New: Deals that have been created in the current month, that are not offboarded.
- 02-Never Booked: Deals that have been created before the current month, without bookings, that are not offboarded.
- 04-Active: Deals that have booking activity in the past 12 months (not reactivated), that are not offboarded.
- 05-Churning: Either Deals that are offboarded in that month or Deals that are becoming inactive because of lack of bookings in the past 12 months
- 06-Inactive: Either Deals that have been previously offboarded or Deals that have not had a booking for more than 12 months.
- 07-Reactivated: Deals that have had a booking in the current month that were inactive or churning before, that are not offboarded.
- Finally, if none of the logic applies, which should not happen, null will be set and a dbt alert will raise.
Since the states of Active, First Time Booked and Reactivated indicate certain booking activity and are
mutually exclusive, the model also provides information of the recency of the bookings by the following
booleans:
- has_been_booked_within_current_month: If a deal has had a booking created in the current month
- has_been_booked_within_last_6_months: If a deal has had a booking created in the past 6 months
- has_been_booked_within_last_12_months: If a deal has had a booking created in the past 12 months
Note that if a deal has had a booking created in a given month, all 3 columns will be true. Similarly,
if the last booking created to a deal was 5 months ago, only the column has_been_booked_in_1_month
will be false; while the other 2 will be true.
Some final considerations:
- It's possible but not common that a Deal gets offboarded on the same month that has had some bookings created.
- It shouldn't happen that a Deal that is Inactive has some bookings created. However, there's few cases in which
this happens likely because of misconfiguration between Hubspot and Core. This should be reported to increase
data quality.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date in which a Deal has a given lifecycle state.
data_tests:
- not_null
- name: id_deal
data_type: character varying
description: Unique identifier of the Account.
data_tests:
- not_null
- name: creation_date_utc
data_type: date
description: Date of when the first host associated to that deal was created.
- name: first_time_booked_date_utc
data_type: date
description: |
Date of the first booking created for a given deal. Can be null if the deal
has never had a booking associated with it.
- name: last_time_booked_date_utc
data_type: date
description: |
Date of the last booking created for a given deal. Can be null if the deal
has never had a booking associated with it. Can be the same as first_time_booked_date_utc
if the deal only had 1 booking in its history.
- name: second_to_last_time_booked_date_utc
data_type: date
description: |
Date of the second-to-last booking created for a given deal, meaning the creation
date of the booking that precedes the last one. It's relevant for the reactivation computation
on the lifecycle. Can be null if the deal has never had a booking associated with it or if
the deal only had 1 booking in its history.
- name: cancellation_date_utc
data_type: date
description: |
Date of when the deal was cancelled, according to Hubspot. This is the date we're considering
for hard offboarding. It can be null, meaning the account has not been offboarded.
- name: deal_lifecycle_state
data_type: character varying
description: |
Contains the lifecycle state of a deal. The accepted values are:
01-New, 02-Never Booked, 04-Active, 05-Churning, 06-Inactive,
07-Reactivated. Failing to implement the logic will result in alert.
data_tests:
- not_null
- accepted_values:
values:
- 01-New
- 02-Never Booked
- 04-Active
- 05-Churning
- 06-Inactive
- 07-Reactivated
- name: has_been_booked_within_current_month
data_type: boolean
description: |
If the deal has had a booking already created in the current month.
Note that if the Booking is created on the 5th day, this column will
be false for the days 1st to 4th, and true from the day 5th onwards.
- name: has_been_booked_within_last_6_months
data_type: boolean
description: |
If the deal has had a booking created in the past 6 months.
- name: has_been_booked_within_last_12_months
data_type: boolean
description: |
If the deal has had a booking created in the past 12 months.
- name: has_been_offboarded
data_type: boolean
description: |
If the deal has been cancelled or not. Note that if the Deal
has been offboarded on the 5th day, this column will be false
for the days 1st to 4th, and true from the day 5th onwards.
- name: int_kpis__dimension_deals
description: |
This model provides the main baseline for deals for KPIs.
It combines deals from both Hubspot and Core. In case of a deal
being present in both systems, Hubspot data will take precedence
in terms of deal name. Besides, the model provides the main billing
country according to core, in case core deals exist. Lastly, the first
date considered as effective date corresponds to the minimum between the
date a deal has gone live according to Hubspot and the first date a user
host has been created according to Core.
columns:
- name: id_deal
data_type: string
description: ID of the account, or deal.
data_tests:
- not_null
- unique
- name: main_deal_name
data_type: string
description: |
Main deal name according to Hubspot. In case of a deal being present
in both systems, Hubspot data will take precedence in terms of deal name.
data_tests:
- not_null
- name: has_active_pms
data_type: boolean
description: |
Does the deal have an active associated PMS.
data_tests:
- not_null
- name: active_pms_list
data_type: string
description: |
Name of the active PMS associated with the deal. It can have more than
one PMS associated with it. It can be null if it doesn't have any PMS associated.
- name: client_type
data_type: string
description: |
Type of client associated with the deal.
data_tests:
- not_null
- accepted_values:
values:
- API
- PLATFORM
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level according to
Core. It can be null if the deal is only present in Hubspot or if the
field is null in Core.
- name: effective_deal_start_date_utc
data_type: date
description: |
Effective start date of the deal, which corresponds to the minimum between the
date a deal has gone live according to Hubspot and the first date a user
host has been created according to Core.
data_tests:
- not_null
- name: effective_deal_start_month
data_type: date
description: |
This field represents the first day of the month of the effective
start date of the deal. This is obtained by truncating the effective
deal start date to the month.
data_tests:
- not_null
- name: hubspot_deal_cancellation_date_utc
data_type: date
description: |
Effective date at which the deal cancelled it's partnership with Superhog.
- name: hubspot_deal_cancellation_month
data_type: date
description: |
This field represents the first day of the month of the cancellation date
of the deal. This is obtained by truncating the cancellation deal date
to the month.
- name: hubspot_listing_segmentation
data_type: integer
description: |
Segment value based on the number of properties managed by the deal
according to what was set in HubSpot.
data_tests:
- accepted_values:
values:
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: int_kpis__dimension_daily_accommodation
description: |
This model computes the deal segmentation per number of
listings in a daily manner.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Specific date in which the segmentation applies.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- name: accommodations_booked_in_12_months
data_type: bigint
description:
Actual volume of listings that have been booked in the past 12 months
for a given deal and date.
- name: int_kpis__metric_daily_created_bookings
description: |
This model computes the Daily Created Bookings at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Bookings have been created.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_bookings
data_type: bigint
description: |
Count of daily bookings created in a given date and per specified dimension.
- name: cancelled_created_bookings
data_type: bigint
description: |
Count of daily bookings created in a given date and per specified dimension
that have been cancelled.
- name: not_cancelled_created_bookings
data_type: bigint
description: |
Count of daily bookings created in a given date and per specified dimension
that have not been cancelled.
- name: int_kpis__metric_monthly_created_bookings
description: |
This model computes the Monthly Created Bookings at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_bookings
data_type: bigint
description: |
Count of accumulated bookings created in a given month
and per specified dimension.
- name: cancelled_created_bookings
data_type: bigint
description: |
Count of accumulated bookings created in a given month
and per specified dimension that have been cancelled.
- name: not_cancelled_created_bookings
data_type: bigint
description: |
Count of accumulated bookings created in a given month
and per specified dimension that have not been cancelled.
- name: int_kpis__metric_mtd_created_bookings
description: |
This model computes the Month-To-Date Created Bookings at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_bookings
data_type: bigint
description: |
Count of accumulated bookings created in a given month up to the
given date and per specified dimension.
- name: cancelled_created_bookings
data_type: bigint
description: |
Count of accumulated bookings created in a given month up to the
given date and per specified dimension that have been cancelled.
- name: not_cancelled_created_bookings
data_type: bigint
description: |
Count of accumulated bookings created in a given month up to the
given date and per specified dimension that have not been cancelled.
- name: int_kpis__agg_monthly_created_bookings
description: |
This model computes the dimension aggregation for
Monthly Created Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- created_bookings
- cancelled_created_bookings
- not_cancelled_created_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_bookings
data_type: bigint
description: The monthly created bookings for a given date, dimension and value.
- name: cancelled_created_bookings
data_type: bigint
description: |
The monthly cancelled created bookings for a given date, dimension and value.
- name: not_cancelled_created_bookings
data_type: bigint
description: |
The monthly not cancelled created bookings for a given date, dimension and value.
- name: cancelled_created_bookings_rate
data_type: decimal
description: |
The monthly rate of cancelled created bookings for a given date, dimension and value.
- name: int_kpis__agg_mtd_created_bookings
description: |
This model computes the dimension aggregation for
Month-To-Date Created Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- created_bookings
- cancelled_created_bookings
- not_cancelled_created_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_bookings
data_type: bigint
description: The month-to-date created bookings for a given date, dimension and value.
- name: cancelled_created_bookings
data_type: bigint
description: |
The month-to-date cancelled created bookings for a given date, dimension and value.
- name: not_cancelled_created_bookings
data_type: bigint
description: |
The month-to-date not cancelled created bookings for a given date, dimension and value.
- name: cancelled_created_bookings_rate
data_type: decimal
description: |
The month-to-date rate of cancelled created bookings for a given date, dimension and value.
- name: int_kpis__metric_daily_created_guest_journeys
description: |
This model computes the Daily Created Guest Journeys at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been created.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys created in a given date and per specified dimension.
- name: int_kpis__metric_monthly_created_guest_journeys
description: |
This model computes the Monthly Created Guest Journeys at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: |
Count of accumulated guest journeys created in a given month
and per specified dimension.
- name: int_kpis__metric_mtd_created_guest_journeys
description: |
This model computes the Month-To-Date Created Guest Journeys at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: |
Count of accumulated guest journeys created in a given month up to the
given date and per specified dimension.
- name: int_kpis__agg_monthly_created_guest_journeys
description: |
This model computes the dimension aggregation for
Monthly Created Guest Journeys.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- created_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: The monthly created guest journeys for a given date, dimension and value.
- name: int_kpis__agg_mtd_created_guest_journeys
description: |
This model computes the dimension aggregation for
Month-To-Date Created Guest Journeys.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- created_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: The month-to-date created guest journeys for a given date, dimension and value.
- name: int_kpis__metric_daily_started_guest_journeys
description: |
This model computes the Daily Started Guest Journeys at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been started.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: started_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys started in a given date and per specified dimension.
- name: int_kpis__metric_monthly_started_guest_journeys
description: |
This model computes the Monthly Started Guest Journeys at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: started_guest_journeys
data_type: bigint
description: |
Count of accumulated guest journeys started in a given month
and per specified dimension.
- name: int_kpis__metric_mtd_started_guest_journeys
description: |
This model computes the Month-To-Date Started Guest Journeys at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: started_guest_journeys
data_type: bigint
description: |
Count of accumulated guest journeys started in a given month up to the
given date and per specified dimension.
- name: int_kpis__agg_monthly_started_guest_journeys
description: |
This model computes the dimension aggregation for
Monthly Started Guest Journeys.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- started_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: started_guest_journeys
data_type: bigint
description: The monthly started guest journeys for a given date, dimension and value.
- name: int_kpis__agg_mtd_started_guest_journeys
description: |
This model computes the dimension aggregation for
Month-To-Date Started Guest Journeys.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- started_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: started_guest_journeys
data_type: bigint
description: The month-to-date started guest journeys for a given date, dimension and value.
- name: int_kpis__metric_daily_completed_guest_journeys
description: |
This model computes the Daily Completed Guest Journeys at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been completed.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: completed_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys completed in a given date and per specified dimension.
- name: int_kpis__metric_monthly_completed_guest_journeys
description: |
This model computes the Monthly Completed Guest Journeys at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: completed_guest_journeys
data_type: bigint
description: |
Count of accumulated guest journeys completed in a given month
and per specified dimension.
- name: int_kpis__metric_mtd_completed_guest_journeys
description: |
This model computes the Month-To-Date Completed Guest Journeys at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: completed_guest_journeys
data_type: bigint
description: |
Count of accumulated guest journeys completed in a given month up to the
given date and per specified dimension.
- name: int_kpis__agg_monthly_completed_guest_journeys
description: |
This model computes the dimension aggregation for
Monthly Completed Guest Journeys.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- completed_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: completed_guest_journeys
data_type: bigint
description: The monthly completed guest journeys for a given date, dimension and value.
- name: int_kpis__agg_mtd_completed_guest_journeys
description: |
This model computes the dimension aggregation for
Month-To-Date Completed Guest Journeys.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- completed_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: completed_guest_journeys
data_type: bigint
description: The month-to-date completed guest journeys for a given date, dimension and value.
- name: int_kpis__metric_daily_guest_journeys_with_payment
description: |
This model computes the Daily Guest Journeys with Payment at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been completed.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: guest_journeys_with_payment
data_type: bigint
description: |
Count of daily guest journeys completed in a given date and per specified dimension.
- name: int_kpis__metric_monthly_guest_journeys_with_payment
description: |
This model computes the Monthly Guest Journeys with Payment at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: guest_journeys_with_payment
data_type: bigint
description: |
Count of accumulated guest journeys completed in a given month
and per specified dimension.
- name: int_kpis__metric_mtd_guest_journeys_with_payment
description: |
This model computes the Month-To-Date Guest Journeys with Payment at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: guest_journeys_with_payment
data_type: bigint
description: |
Count of accumulated guest journeys completed in a given month up to the
given date and per specified dimension.
- name: int_kpis__agg_monthly_guest_journeys_with_payment
description: |
This model computes the dimension aggregation for
Monthly Guest Journeys with Payment.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- guest_journeys_with_payment
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: guest_journeys_with_payment
data_type: bigint
description: The monthly guest journeys with payment for a given date, dimension and value.
- name: int_kpis__agg_mtd_guest_journeys_with_payment
description: |
This model computes the dimension aggregation for
Month-To-Date Guest Journeys with Payment.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- guest_journeys_with_payment
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: guest_journeys_with_payment
data_type: bigint
description: The month-to-date guest journeys with payment for a given date, dimension and value.
- name: int_kpis__metric_daily_guest_payments
description: |
This model computes the Daily Guest Payments at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- has_id_check,
- business_scope
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- has_id_check
- business_scope
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been completed.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: has_id_check
data_type: string
description: Does the verification in the guest journey
includes Government Id Check for the bookings.
data_tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: deposit_fees_in_gbp
data_type: decimal
description: |
Sum of deposit fees paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: waiver_payments_in_gbp
data_type: decimal
description: |
Sum of waiver payments paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: checkin_cover_fees_in_gbp
data_type: decimal
description: |
Sum of checkin cover fees paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: total_guest_payments_in_gbp
data_type: decimal
description: |
Sum of total payments paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: int_kpis__metric_monthly_guest_payments
description: |
This model computes the Monthly Guest Payments at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- has_id_check,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- has_id_check
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: has_id_check
data_type: string
description: Does the verification in the guest journey
includes Government Id Check for the bookings.
data_tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: deposit_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated deposit fees paid by guests, without taxes,
in GBP in a given month and per specified dimension.
- name: waiver_payments_in_gbp
data_type: decimal
description: |
Sum of accumulated waiver payments paid by guests, without taxes,
in GBP in a given month and per specified dimension.
- name: checkin_cover_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated checkin cover fees by guests, without taxes,
in GBP in a given month and per specified dimension.
- name: total_guest_payments_in_gbp
data_type: decimal
description: |
Sum of accumulated total payments paid by guests, without taxes,
in GBP in a given month and per specified dimension.
- name: int_kpis__metric_mtd_guest_payments
description: |
This model computes the Month-To-Date Guest Payments at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- has_id_check,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- has_id_check
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: has_id_check
data_type: string
description: Does the verification in the guest journey
includes Government Id Check for the bookings.
data_tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: deposit_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated deposit fees paid by guests, without taxes,
in GBP in a given month up to the given date and per specified dimension.
- name: waiver_payments_in_gbp
data_type: decimal
description: |
Sum of accumulated waiver payments paid by guests, without taxes,
in GBP in a given month up to the given date and per specified dimension.
- name: checkin_cover_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated checkin cover fees by guests, without taxes,
in GBP in a given month up to the given date and per specified dimension.
- name: total_guest_payments_in_gbp
data_type: decimal
description: |
Sum of accumulated total payments paid by guests, without taxes,
in GBP in a given month up to the given date and per specified dimension.
- name: int_kpis__agg_monthly_guest_payments
description: |
This model computes the dimension aggregation for
Monthly Guest Payments.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- deposit_fees_in_gbp
- waiver_payments_in_gbp
- checkin_cover_fees_in_gbp
- total_guest_payments_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- by_has_id_check
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: deposit_fees_in_gbp
data_type: decimal
description: |
The monthly deposit fees paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: waiver_payments_in_gbp
data_type: decimal
description: |
The monthly waiver payments paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: checkin_cover_fees_in_gbp
data_type: decimal
description: |
The monthly checkin cover fees paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: total_guest_payments_in_gbp
data_type: decimal
description: |
The monthly total payments paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: int_kpis__agg_mtd_guest_payments
description: |
This model computes the dimension aggregation for
Month-To-Date Guest Payments.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- deposit_fees_in_gbp
- waiver_payments_in_gbp
- checkin_cover_fees_in_gbp
- total_guest_payments_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- by_has_id_check
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: deposit_fees_in_gbp
data_type: decimal
description: |
The month-to-date deposit fees paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: waiver_payments_in_gbp
data_type: decimal
description: |
The month-to-date waiver payments paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: checkin_cover_fees_in_gbp
data_type: decimal
description: |
The month-to-date checkin cover fees paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: total_guest_payments_in_gbp
data_type: decimal
description: |
The month-to-date total payments paid by guests, without taxes, in GBP
for a given range date, dimension and value.
- name: int_kpis__metric_daily_check_out_bookings
description: |
This model computes the Daily Check-out Bookings at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Bookings have been checked-out.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: check_out_bookings
data_type: bigint
description: |
Count of daily bookings checked-out in a given date and per specified dimension.
- name: cancelled_check_out_bookings
data_type: bigint
description: |
Count of daily bookings checked-out in a given date and per specified dimension
that have been cancelled.
- name: not_cancelled_check_out_bookings
data_type: bigint
description: |
Count of daily bookings checked-out in a given date and per specified dimension
that have not been cancelled.
- name: int_kpis__metric_monthly_check_out_bookings
description: |
This model computes the Monthly Check-out Bookings at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: check_out_bookings
data_type: bigint
description: |
Count of accumulated bookings checked-out in a given month
and per specified dimension.
- name: cancelled_check_out_bookings
data_type: bigint
description: |
Count of accumulated bookings checked-out in a given month
and per specified dimension that have been cancelled.
- name: not_cancelled_check_out_bookings
data_type: bigint
description: |
Count of accumulated bookings checked-out in a given month
and per specified dimension that have not been cancelled.
- name: int_kpis__metric_mtd_check_out_bookings
description: |
This model computes the Month-To-Date Check-out Bookings at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: check_out_bookings
data_type: bigint
description: |
Count of accumulated bookings checked-out in a given month up to the
given date and per specified dimension.
- name: cancelled_check_out_bookings
data_type: bigint
description: |
Count of accumulated bookings checked-out in a given month up to the
given date and per specified dimension that have been cancelled.
- name: not_cancelled_check_out_bookings
data_type: bigint
description: |
Count of accumulated bookings checked-out in a given month up to the
given date and per specified dimension that have not been cancelled.
- name: int_kpis__agg_monthly_check_out_bookings
description: |
This model computes the dimension aggregation for
Monthly Check-out Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- check_out_bookings
- cancelled_check_out_bookings
- not_cancelled_check_out_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: check_out_bookings
data_type: bigint
description: The monthly checked-out bookings for a given date, dimension and value.
- name: cancelled_check_out_bookings
data_type: bigint
description: |
The monthly cancelled checked-out bookings for a given date, dimension and value.
- name: not_cancelled_check_out_bookings
data_type: bigint
description: |
The monthly not cancelled checked-out bookings for a given date, dimension and value.
- name: cancelled_check_out_bookings_rate
data_type: decimal
description: |
The monthly rate of cancelled checked-out bookings for a given date, dimension and value.
- name: int_kpis__agg_mtd_check_out_bookings
description: |
This model computes the dimension aggregation for
Month-To-Date Check-out Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- check_out_bookings
- cancelled_check_out_bookings
- not_cancelled_check_out_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: check_out_bookings
data_type: bigint
description: The month-to-date checked-out bookings for a given date, dimension and value.
- name: cancelled_check_out_bookings
data_type: bigint
description: |
The month-to-date cancelled checked-out bookings for a given date, dimension and value.
- name: not_cancelled_check_out_bookings
data_type: bigint
description: |
The month-to-date not cancelled checked-out bookings for a given date, dimension and value.
- name: cancelled_check_out_bookings_rate
data_type: decimal
description: |
The month-to-date rate of cancelled checked-out bookings for a given date, dimension and value.
- name: int_kpis__metric_daily_billable_bookings
description: |
This model computes the Daily Billable Bookings at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Bookings have been billable.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: billable_bookings
data_type: bigint
description: |
Count of daily bookings billable in a given date and per specified dimension.
- name: int_kpis__metric_monthly_billable_bookings
description: |
This model computes the Monthly Billable Bookings at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: billable_bookings
data_type: bigint
description: |
Count of accumulated bookings billable in a given month
and per specified dimension.
- name: int_kpis__metric_mtd_billable_bookings
description: |
This model computes the Month-To-Date Billable Bookings at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: billable_bookings
data_type: bigint
description: |
Count of accumulated bookings billable in a given month up to the
given date and per specified dimension.
- name: int_kpis__agg_monthly_billable_bookings
description: |
This model computes the dimension aggregation for
Monthly Billable Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- billable_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: billable_bookings
data_type: bigint
description: The monthly billable bookings for a given date, dimension and value.
- name: int_kpis__agg_mtd_billable_bookings
description: |
This model computes the dimension aggregation for
Month-To-Date Billable Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- billable_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: billable_bookings
data_type: bigint
description: The month-to-date billable bookings for a given date, dimension and value.
- name: int_kpis__metric_daily_check_in_attributed_guest_journeys
description: |
This model computes Guest Journey metrics at the deepest granularity
level for the Guest Products KPIs.
This model uses the Check-In date of the bookings for the date attribute.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- has_payment,
- has_id_check.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- has_payment
- has_id_check
columns:
- name: date
data_type: date
description: Date of Check-In of the bookings for the guest journeys.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: has_payment
data_type: string
description: Has there been any guest payments on the guest journey.
data_tests:
- not_null
- accepted_values:
values:
- W/O Payment
- With Payment
- name: has_id_check
data_type: string
description: Does the verification in the guest journey
includes Government Id Check for the bookings.
data_tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys created, excluding cancelled bookings,
in a given date and per specified dimension.
- name: started_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys started, excluding cancelled bookings,
in a given date and per specified dimension.
- name: completed_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys completed, excluding cancelled bookings,
in a given date and per specified dimension.
- name: created_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys created in a given date and
per specified dimension.
- name: started_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys started in a given date and
per specified dimension.
- name: completed_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys completed in a given date and
per specified dimension.
- name: count_csat_score
data_type: bigint
description: |
Count of daily guest journeys with CSAT (customer satisfaction score)
in a given date and per specified dimension.
- name: average_csat_score
data_type: bigint
description: |
Average daily CSAT score in a given date and per specified dimension.
- name: int_kpis__metric_daily_host_resolutions
description: |
This model computes the Daily Host Resolutions at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when Host Resolutions transaction happened.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: xero_host_resolution_payment_count
data_type: bigint
description: |
Count of daily Host Resolution Payment Count in a given date and per specified dimension.
- name: xero_host_resolution_amount_paid_in_gbp
data_type: decimal
description: |
Sum of daily Host Resolution Amount Paid, in GBP, in a given
date and per specified dimension.
- name: int_kpis__metric_monthly_host_resolutions
description: |
This model computes the Monthly Host Resolutions at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: xero_host_resolution_payment_count
data_type: bigint
description: |
Count of accumulated Host Resolution Payment Count in a
given month and per specified dimension.
- name: xero_host_resolution_amount_paid_in_gbp
data_type: decimal
description: |
Sum of accumulated Host Resolution Amount Paid, in GBP, in a
given month and per specified dimension.
- name: int_kpis__metric_mtd_host_resolutions
description: |
This model computes the Month-To-Date Host Resolutions at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: xero_host_resolution_payment_count
data_type: bigint
description: |
Count of accumulated Host Resolution Payment Count in a
given month up to the given date and per specified dimension.
- name: xero_host_resolution_amount_paid_in_gbp
data_type: decimal
description: |
Sum of accumulated Host Resolution Amount Paid, in GBP, in a
given month up to the given date and per specified dimension.
- name: int_kpis__agg_monthly_host_resolutions
description: |
This model computes the dimension aggregation for
Monthly Host Resolutions.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- xero_host_resolution_payment_count
- xero_host_resolution_amount_paid_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: xero_host_resolution_payment_count
data_type: bigint
description: |
The monthly Host Resolution Payment Count for a given date, dimension and value.
- name: xero_host_resolution_amount_paid_in_gbp
data_type: decimal
description: |
The monthly Host Resolution Amount Paid, in GBP, for a
given date, dimension and value.
- name: int_kpis__agg_mtd_host_resolutions
description: |
This model computes the dimension aggregation for
Month-To-Date Host Resolutions.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- xero_host_resolution_payment_count
- xero_host_resolution_amount_paid_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: xero_host_resolution_payment_count
data_type: bigint
description: |
The month-to-date Host Resolution Payment Count for a given date, dimension and value.
- name: xero_host_resolution_amount_paid_in_gbp
data_type: decimal
description: |
The month-to-date Host Resolution Amount Paid, in GBP, for a
given date, dimension and value.
- name: int_kpis__metric_daily_invoiced_revenue
description: |
This model computes the Daily Invoiced Revenue at the deepest granularity.
The logic behind this model is mostly retrieving different revenue sources
that are invoiced to the hosts. This considers both Invoices and Credit Notes,
thus metrics correspond to the net amount.
Data is retrieved by account codes following accounting standards, and is
aggregated at different levels of business revenue understanding.
Only documents with status equal to Authorised or Paid are considered. Revenue is
computed without taxes, in GBP. Revenue is attributed to the document issued date,
thus it might show some differences vs. financials since we do not consider accrued
revenue.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal,
- business_scope.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date of when the document was issued.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: xero_basic_protection_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Basic Protection Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_waiver_pro_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Waiver Pro Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_id_verification_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily ID Verification Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_protection_plus_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Protection Pro Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_screening_plus_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Screening Plus Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_sex_offenders_check_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Sex Offenders Check Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_protection_pro_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Protection Pro Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_basic_screening_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Basic Screening Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is a New
Dashboard service.
- name: xero_booking_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Booking Net Fees, in GBP, without taxes
in a given date and per specified dimension.
- name: xero_listing_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Listing Net Fees, in GBP, without taxes
in a given date and per specified dimension.
- name: xero_verification_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Verification Net Fees, in GBP, without taxes
in a given date and per specified dimension.
- name: xero_operator_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Operator Net Fees, which include New Dash Services,
Booking, Listing and Verification Net Fees for Old Dash;
in GBP, without taxes in a given date and per specified dimension.
Partial data of 2022 corresponds to revenue categorised as Other Revenue
according to the financials.
- name: xero_e_deposit_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily E-Deposit Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is an
API service.
- name: xero_athena_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Athena (Guesty) Net Fees, in GBP, without taxes
in a given date and per specified dimension. This is an
API service.
- name: xero_guesty_resolutions_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Guesty Resolutions Net Fees, in GBP, without taxes
in a given date and per specified dimension.
- name: xero_guesty_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily Athena (Guesty) Net Fees and Guesty Resolutions
Net Fees, in GBP, without taxes in a given date and per specified
dimension.
- name: xero_apis_net_fees_in_gbp
data_type: decimal
description: |
Sum of daily API Net Fees, which include E-Deposit,
and Athena (Guesty) Net Fees, in GBP, without taxes
in a given date and per specified dimension.
- name: xero_waiver_paid_back_to_host_in_gbp
data_type: decimal
description: |
Sum of daily Waiver Amount Paid Back to Hosts, in GBP,
without taxes in a given date and per specified dimension.
- name: int_kpis__metric_monthly_invoiced_revenue
description: |
This model computes the Monthly Invoiced Revenue at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: xero_basic_protection_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Basic Protection Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_waiver_pro_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Waiver Pro Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_id_verification_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated ID Verification Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_protection_plus_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Protection Plus Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_screening_plus_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Screening Plus Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_sex_offenders_check_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Sex Offenders Check Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_protection_pro_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Protection Pro Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_basic_screening_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Basic Screening Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is a New
Dashboard service.
- name: xero_booking_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Booking Net Fees, in GBP, without taxes
in a given month and per specified dimension.
- name: xero_listing_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Listing Net Fees, in GBP, without taxes
in a given month and per specified dimension.
- name: xero_verification_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Verification Net Fees, in GBP, without taxes
in a given month and per specified dimension.
- name: xero_operator_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Operator Net Fees, which include New Dash Services,
Booking, Listing and Verification Net Fees for Old Dash;
in GBP, without taxes in a given month and per specified dimension.
Partial data of 2022 corresponds to revenue categorised as Other Revenue
according to the financials.
- name: xero_e_deposit_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated E-Deposit Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is an
API service.
- name: xero_athena_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Athena (Guesty) Net Fees, in GBP, without taxes
in a given month and per specified dimension. This is an
API service.
- name: xero_guesty_resolutions_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Guesty Resolutions Net Fees, in GBP, without taxes
in a given month and per specified dimension.
- name: xero_guesty_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Athena (Guesty) Net Fees and Guesty Resolutions
Net Fees, in GBP, without taxes in a given month and per specified
dimension.
- name: xero_waiver_paid_back_to_host_in_gbp
data_type: decimal
description: |
Sum of accumulated Waiver Amount Paid Back to Hosts, in GBP,
without taxes in a given month and per specified dimension.
- name: int_kpis__metric_mtd_invoiced_revenue
description: |
This model computes the Month-To-Date Invoiced Revenue at the
deepest granularity.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- id_deal,
- business_scope,
- active_accommodations_per_deal_segmentation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: xero_basic_protection_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Basic Protection Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_waiver_pro_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Waiver Pro Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_id_verification_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated ID Verification Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_protection_plus_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Protection Plus Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_screening_plus_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Screening Plus Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_sex_offenders_check_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Sex Offenders Check Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_protection_pro_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Protection Pro Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_basic_screening_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Basic Screening Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is a New Dashboard service.
- name: xero_booking_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Booking Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
- name: xero_listing_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Listing Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
- name: xero_verification_net_fees_in_gbp
data_type: decimal
description: |
Sum of accumulated Verification Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
- name: xero_operator_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Operator Net Fees, which include New Dash Services,
Booking, Listing and Verification Net Fees for Old Dash;
in GBP, without taxes in a given month up to the given date
and per specified dimension.
Partial data of 2022 corresponds to revenue categorised as Other Revenue
according to the financials.
- name: xero_e_deposit_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated E-Deposit Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is an API service.
- name: xero_athena_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Athena (Guesty) Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
This is an API service.
- name: xero_guesty_resolutions_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Guesty Resolutions Net Fees, in GBP, without taxes
in a given month up to the given date and per specified dimension.
- name: xero_guesty_net_fees_in_gbp
data_type: decimal
description: |
Sum of accummulated Athena (Guesty) Net Fees and Guesty Resolutions
Net Fees, in GBP, without taxes in a given month up to the given date
and per specified dimension.
- name: xero_waiver_paid_back_to_host_in_gbp
data_type: decimal
description: |
Sum of accumulated Waiver Amount Paid Back to Hosts, in GBP,
without taxes in a given month up to the given date and per
specified dimension.
- name: int_kpis__agg_monthly_invoiced_revenue
description: |
This model computes the dimension aggregation for
Monthly Invoiced Revenue.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- xero_basic_protection_net_fees_in_gbp
- xero_waiver_pro_net_fees_in_gbp
- xero_id_verification_net_fees_in_gbp
- xero_protection_plus_net_fees_in_gbp
- xero_screening_plus_net_fees_in_gbp
- xero_sex_offenders_check_net_fees_in_gbp
- xero_protection_pro_net_fees_in_gbp
- xero_basic_screening_net_fees_in_gbp
- xero_booking_net_fees_in_gbp
- xero_listing_net_fees_in_gbp
- xero_verification_net_fees_in_gbp
- xero_operator_net_fees_in_gbp
- xero_e_deposit_net_fees_in_gbp
- xero_athena_net_fees_in_gbp
- xero_guesty_resolutions_net_fees_in_gbp
- xero_guesty_net_fees_in_gbp
- xero_apis_net_fees_in_gbp
- xero_waiver_paid_back_to_host_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: xero_basic_protection_net_fees_in_gbp
data_type: decimal
description: |
The monthly Basic Protection Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_waiver_pro_net_fees_in_gbp
data_type: decimal
description: |
The monthly Waiver Pro Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_id_verification_net_fees_in_gbp
data_type: decimal
description: |
The monthly ID Verification Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_protection_plus_net_fees_in_gbp
data_type: decimal
description: |
The monthly Protection Plus Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_screening_plus_net_fees_in_gbp
data_type: decimal
description: |
The monthly Screening Plus Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_sex_offenders_check_net_fees_in_gbp
data_type: decimal
description: |
The monthly Sex Offenders Check Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_protection_pro_net_fees_in_gbp
data_type: decimal
description: |
The monthly Protection Pro Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is a New Dashboard service.
- name: xero_basic_screening_net_fees_in_gbp
data_type: decimal
description: |
The monthly Basic Screening Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is a New Dashboard service.
- name: xero_booking_net_fees_in_gbp
data_type: decimal
description: |
The monthly Booking Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_listing_net_fees_in_gbp
data_type: decimal
description: |
The monthly Listing Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_verification_net_fees_in_gbp
data_type: decimal
description: |
The monthly Verification Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_operator_net_fees_in_gbp
data_type: decimal
description: |
The monthly Operator Net Fees, which include New Dash Services,
Booking, Listing and Verification Net Fees for Old Dash;
in GBP, without taxes for a given date, dimension and value.
Partial data of 2022 corresponds to revenue categorised as Other Revenue
according to the financials.
- name: xero_e_deposit_net_fees_in_gbp
data_type: decimal
description: |
The monthly E-Deposit Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is an API service.
- name: xero_athena_net_fees_in_gbp
data_type: decimal
description: |
The monthly Athena (Guesty) Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is an API service.
- name: xero_guesty_resolutions_net_fees_in_gbp
data_type: decimal
description: |
The monthly Guesty Resolutions Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_guesty_net_fees_in_gbp
data_type: decimal
description: |
The monthly Athena (Guesty) Net Fees and Guesty Resolutions
Net Fees, in GBP, without taxes for a given date, dimension and value.
- name: xero_waiver_paid_back_to_host_in_gbp
data_type: decimal
description: |
The monthly Waiver Amount Paid Back to Hosts, in GBP, without taxes
for a given date, dimension and value.
- name: int_kpis__agg_mtd_invoiced_revenue
description: |
This model computes the dimension aggregation for
Month-To-Date Invoiced Revenue.
The primary key of this model is end_date, dimension
and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- xero_basic_protection_net_fees_in_gbp
- xero_waiver_pro_net_fees_in_gbp
- xero_id_verification_net_fees_in_gbp
- xero_protection_plus_net_fees_in_gbp
- xero_screening_plus_net_fees_in_gbp
- xero_sex_offenders_check_net_fees_in_gbp
- xero_protection_pro_net_fees_in_gbp
- xero_basic_screening_net_fees_in_gbp
- xero_booking_net_fees_in_gbp
- xero_listing_net_fees_in_gbp
- xero_verification_net_fees_in_gbp
- xero_operator_net_fees_in_gbp
- xero_e_deposit_net_fees_in_gbp
- xero_athena_net_fees_in_gbp
- xero_guesty_resolutions_net_fees_in_gbp
- xero_guesty_net_fees_in_gbp
- xero_apis_net_fees_in_gbp
- xero_waiver_paid_back_to_host_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: xero_basic_protection_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Basic Protection Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_waiver_pro_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Waiver Pro Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_id_verification_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date ID Verification Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_protection_plus_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Protection Plus Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_screening_plus_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Screening Plus Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_sex_offenders_check_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Sex Offenders Check Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_protection_pro_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Protection Pro Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is a New Dashboard service.
- name: xero_basic_screening_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Basic Screening Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is a New Dashboard service.
- name: xero_booking_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Booking Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_listing_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Listing Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_verification_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Verification Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_operator_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Operator Net Fees, which include New Dash Services,
Booking, Listing and Verification Net Fees for Old Dash;
in GBP, without taxes for a given date, dimension and value.
Partial data of 2022 corresponds to revenue categorised as Other Revenue
according to the financials.
- name: xero_e_deposit_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date E-Deposit Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is an API service.
- name: xero_athena_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Athena (Guesty) Net Fees, in GBP, without taxes
for a given date, dimension and value.
This is an API service.
- name: xero_guesty_resolutions_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Guesty Resolutions Net Fees, in GBP, without taxes
for a given date, dimension and value.
- name: xero_guesty_net_fees_in_gbp
data_type: decimal
description: |
The month-to-date Athena (Guesty) Net Fees and Guesty Resolutions
Net Fees, in GBP, without taxes for a given date, dimension and value.
- name: xero_waiver_paid_back_to_host_in_gbp
data_type: decimal
description: |
The month-to-date Waiver Amount Paid Back to Hosts, in GBP, without taxes
for a given date, dimension and value.
- name: int_kpis__metric_daily_deals
description: |
This model computes the Daily Deal metrics at the deepest granularity.
Be aware that this Deal entity will differ from how the rest of models
usually operate. This is because we compute Deal metrics, thus it does
not make sense to compute these at Deal level.
Also, Deal metrics at daily level already contain the time dimension
aggregates needed, thus we won't have mtd or monthly equivalent models,
but rather just select from this daily model the needed days to recover
the necessary information.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- main_billing_country_iso_3_per_deal,
- business_scope,
- active_accommodations_per_deal_segmentation
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- main_billing_country_iso_3_per_deal
- business_scope
- active_accommodations_per_deal_segmentation
columns:
- name: date
data_type: date
description: Date containing the Deal metrics.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: new_deals
data_type: bigint
description: |
Count of new deals in a given date and per specified dimension.
- name: never_booked_deals
data_type: bigint
description: |
Count of never booked deals in a given date and per specified dimension.
- name: active_deals
data_type: bigint
description: |
Count of active deals in a given date and per specified dimension.
- name: inactive_deals
data_type: bigint
description: |
Count of inactive deals in a given date and per specified dimension.
- name: churning_deals
data_type: bigint
description: |
Count of churning deals in a given date and per specified dimension.
- name: reactivated_deals
data_type: bigint
description: |
Count of reactivated deals in a given date and per specified dimension.
- name: deals_booked_in_month
data_type: bigint
description: |
Count of deals booked within the month in a given date and per specified dimension.
- name: deals_booked_in_6_months
data_type: bigint
description: |
Count of deals booked within the past 6 months in a given date and per specified dimension.
- name: deals_booked_in_12_months
data_type: bigint
description: |
Count of deals booked within the past 12 months in a given date and per specified dimension.
- name: live_deals
data_type: bigint
description: |
Count of live deals in a given date and per specified dimension.
This accounts for New Deals, Active Deals and Reactivated Deals.
- name: int_kpis__agg_daily_deals
description: |
This model computes the dimension aggregation for
Daily Deal metrics.
The primary key of this model is date, dimension
and dimension_value.
Be aware that this Deal entity will differ from how the rest of models
usually operate. This is because we compute Deal metrics, thus it does
not make sense to compute these at Deal level.
Also, Deal metrics at daily level already contain the time dimension
aggregates needed, thus we won't have mtd or monthly equivalent models,
but rather just select from this daily model the needed days to recover
the necessary information.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- dimension
- dimension_value
columns:
- name: date
data_type: date
description: Date containing the Deal metrics.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- new_deals
- never_booked_deals
- active_deals
- churning_deals
- inactive_deals
- reactivated_deals
- deals_booked_in_month
- deals_booked_in_6_months
- deals_booked_in_12_months
- live_deals
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: is_end_of_month
data_type: boolean
description: True if it's end of month, false otherwise.
data_tests:
- not_null
- name: is_current_month
data_type: boolean
description: |
True if the date is within the current month, false otherwise.
data_tests:
- not_null
- name: is_month_to_date
data_type: boolean
description: |
True if the date is within the scope of month-to-date, false otherwise.
The scope of month-to-date takes into account both 1) a date being in
the current month or 2) a date corresponding to the same month of the
previous year, which day number cannot be higher than yesterday's day
number.
data_tests:
- not_null
- name: new_deals
data_type: bigint
description: |
Count of new deals for a given date, dimension and value.
- name: never_booked_deals
data_type: bigint
description: |
Count of never booked deals for a given date, dimension and value.
- name: active_deals
data_type: bigint
description: |
Count of active deals for a given date, dimension and value.
- name: inactive_deals
data_type: bigint
description: |
Count of inactive deals for a given date, dimension and value.
- name: churning_deals
data_type: bigint
description: |
Count of churning deals for a given date, dimension and value.
- name: reactivated_deals
data_type: bigint
description: |
Count of reactivated deals for a given date, dimension and value.
- name: deals_booked_in_month
data_type: bigint
description: |
Count of deals booked within the month for a given date, dimension and value.
- name: deals_booked_in_6_months
data_type: bigint
description: |
Count of deals booked within the past 6 months for a given date, dimension and value.
- name: deals_booked_in_12_months
data_type: bigint
description: |
Count of deals booked within the past 12 months for a given date, dimension and value.
- name: live_deals
data_type: bigint
description: |
Count of live deals in a given date and per specified dimension.
This accounts for New Deals, Never Booked Deals, Active Deals and Reactivated Deals.
- name: int_kpis__metric_daily_listings
description: |
This model computes the Daily Listing metrics at the deepest granularity.
Listing metrics at daily level already contain the time dimension
aggregates needed, thus we won't have mtd or monthly equivalent models,
but rather just select from this daily model the needed days to recover
the necessary information.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- business_scope
- id_deal
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- business_scope
columns:
- name: date
data_type: date
description: Date containing the Listing metrics.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: business_scope
data_type: string
description: |
Business scope identifying the metric source.
data_tests:
- not_null
- accepted_values:
values:
- "Old Dash"
- "New Dash"
- "API"
- "UNSET"
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Listing level.
data_tests:
- not_null
- name: new_listings
data_type: bigint
description: |
Count of new listings in a given date and per specified dimension.
- name: never_booked_listings
data_type: bigint
description: |
Count of never booked listings in a given date and per specified dimension.
- name: first_time_booked_listings
data_type: bigint
description: |
Count of first-time booked listings in a given date and per specified dimension.
- name: active_listings
data_type: bigint
description: |
Count of active listings in a given date and per specified dimension.
- name: inactive_listings
data_type: bigint
description: |
Count of inactive listings in a given date and per specified dimension.
- name: churning_listings
data_type: bigint
description: |
Count of churning listings in a given date and per specified dimension.
- name: reactivated_listings
data_type: bigint
description: |
Count of reactivated listings in a given date and per specified dimension.
- name: listings_booked_in_month
data_type: bigint
description: |
Count of listings booked within the month in a given date and per specified dimension.
- name: listings_booked_in_6_months
data_type: bigint
description: |
Count of listings booked within the past 6 months in a given date and per specified dimension.
- name: listings_booked_in_12_months
data_type: bigint
description: |
Count of listings booked within the past 12 months in a given date and per specified dimension.
- name: int_kpis__agg_daily_listings
description: |
This model computes the dimension aggregation for
Daily Listing metrics.
The primary key of this model is date, dimension
and dimension_value.
Listing metrics at daily level already contain the time dimension
aggregates needed, thus we won't have mtd or monthly equivalent models,
but rather just select from this daily model the needed days to recover
the necessary information.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- dimension
- dimension_value
columns:
- name: date
data_type: date
description: Date containing the Listing metrics.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- new_listings
- never_booked_listings
- first_time_booked_listings
- active_listings
- churning_listings
- inactive_listings
- reactivated_listings
- listings_booked_in_month
- listings_booked_in_6_months
- listings_booked_in_12_months
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_business_scope
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: is_end_of_month
data_type: boolean
description: True if it's end of month, false otherwise.
data_tests:
- not_null
- name: is_current_month
data_type: boolean
description: |
True if the date is within the current month, false otherwise.
data_tests:
- not_null
- name: is_month_to_date
data_type: boolean
description: |
True if the date is within the scope of month-to-date, false otherwise.
The scope of month-to-date takes into account both 1) a date being in
the current month or 2) a date corresponding to the same month of the
previous year, which day number cannot be higher than yesterday's day
number.
data_tests:
- not_null
- name: new_listings
data_type: bigint
description: |
Count of new listings for a given date, dimension and value.
- name: never_booked_listings
data_type: bigint
description: |
Count of never booked listings for a given date, dimension and value.
- name: first_time_booked_listings
data_type: bigint
description: |
Count of first-time booked listings for a given date, dimension and value.
- name: active_listings
data_type: bigint
description: |
Count of active listings for a given date, dimension and value.
- name: inactive_listings
data_type: bigint
description: |
Count of inactive listings for a given date, dimension and value.
- name: churning_listings
data_type: bigint
description: |
Count of churning listings for a given date, dimension and value.
- name: reactivated_listings
data_type: bigint
description: |
Count of reactivated listings for a given date, dimension and value.
- name: listings_booked_in_month
data_type: bigint
description: |
Count of listings booked within the month for a given date, dimension and value.
- name: listings_booked_in_6_months
data_type: bigint
description: |
Count of listings booked within the past 6 months for a given date, dimension and value.
- name: listings_booked_in_12_months
data_type: bigint
description: |
Count of listings booked within the past 12 months for a given date, dimension and value.
- name: int_kpis__dimension_date_product_guest
description: |
This model computes a cross join of dates with all combinations of
guest products dimensions.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date_day
- has_payment
- has_id_check
- main_billing_country_iso_3_per_deal
columns:
- name: date_day
data_type: date
description: "Date of when Guest Journeys have been completed."
data_tests:
- not_null
- name: date_week
data_type: string
description: "Week number of when Guest Journeys have been completed."
data_tests:
- not_null
- name: has_payment
data_type: string
description: Has there been any guest payments on the guest journey.
data_tests:
- not_null
- accepted_values:
values:
- W/O Payment
- With Payment
- name: has_id_check
data_type: string
description: Does the verification in the guest journey
includes Government Id Check for the bookings.
data_tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host.
data_tests:
- not_null
- name: int_kpis__product_guest_daily_metrics
description: |
This model computes the Daily Guest Metrics at the deepest granularity.
Here all metrics are attributed to the Check-in Date of the associated
booking, except for payments which are attributed to payment date.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date_day,
- py_date_day,
- id_deal,
- has_id_check,
- main_billing_country_iso_3_per_deal.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date_day
- py_date_day
- has_payment
- has_id_check
- main_billing_country_iso_3_per_deal
columns:
- name: date_day
data_type: date
description: "Date of when Guest Journeys have been completed."
data_tests:
- not_null
- name: date_week
data_type: string
description: "Week number of when Guest Journeys have been completed."
data_tests:
- not_null
- name: py_date_day
data_type: date
description: |
Date on the previous year of when Guest Journeys have been completed.
Note that this date can be NULL for leap days (29th February)
- name: has_payment
data_type: string
description: Has there been any guest payments on the guest journey.
data_tests:
- not_null
- accepted_values:
values:
- W/O Payment
- With Payment
- name: has_id_check
data_type: string
description: Does the verification in the guest journey
includes Government Id Check for the bookings.
data_tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host.
data_tests:
- not_null
- name: created_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys created, excluding cancelled bookings,
in a given date and per specified dimension.
- name: started_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys started, excluding cancelled bookings,
in a given date and per specified dimension.
- name: completed_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys completed, excluding cancelled bookings,
in a given date and per specified dimension.
- name: created_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys created in a given date and
per specified dimension.
- name: started_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys started in a given date and
per specified dimension.
- name: completed_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys completed in a given date and
per specified dimension.
- name: total_csat_score_count
data_type: bigint
description: |
Count of daily guest journeys with CSAT (customer satisfaction score)
in a given date and per specified dimension.
- name: average_csat_score
data_type: bigint
description: |
Average daily CSAT score in a given date and per specified dimension.
- name: deposit_fees_in_gbp
data_type: decimal
description: |
Sum of deposit fees paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: waiver_payments_in_gbp
data_type: decimal
description: |
Sum of waiver payments paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: checkin_cover_fees_in_gbp
data_type: decimal
description: |
Sum of checkin cover fees paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: total_guest_payments_in_gbp
data_type: decimal
description: |
Sum of total payments paid by guests, without taxes, in GBP
in a given date and per specified dimension.
- name: py_created_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys created (excluding canceled bookings)
on the same date in the previous year, segmented by the specified dimension.
- name: py_started_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys started (excluding canceled bookings)
on the same date in the previous year, segmented by the specified dimension.
- name: py_completed_guest_journeys_not_cancelled
data_type: bigint
description: |
Count of daily guest journeys completed (excluding canceled bookings)
on the same date in the previous year, segmented by the specified dimension.
- name: py_created_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys created on the same date in the previous year,
segmented by the specified dimension.
- name: py_started_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys started on the same date in the previous year,
segmented by the specified dimension.
- name: py_completed_guest_journeys
data_type: bigint
description: |
Count of daily guest journeys completed on the same date in the previous year,
segmented by the specified dimension.
- name: py_total_csat_score_count
data_type: bigint
description: |
Count of daily guest journeys with CSAT (customer satisfaction score)
on the same date in the previous year, segmented by the specified dimension.
- name: py_average_csat_score
data_type: bigint
description: |
Average daily CSAT score on the same date in the previous year,
segmented by the specified dimension.
- name: py_deposit_fees_in_gbp
data_type: decimal
description: |
Sum of deposit fees paid by guests, excluding taxes, in GBP
on the same date in the previous year, segmented by the specified dimension.
- name: py_waiver_payments_in_gbp
data_type: decimal
description: |
Sum of waiver payments paid by guests, excluding taxes, in GBP
on the same date in the previous year, segmented by the specified dimension.
- name: py_checkin_cover_fees_in_gbp
data_type: decimal
description: |
Sum of check-in cover fees paid by guests, excluding taxes, in GBP
on the same date in the previous year, segmented by the specified dimension.
- name: py_total_guest_payments_in_gbp
data_type: decimal
description: |
Sum of total payments paid by guests, excluding taxes, in GBP
on the same date in the previous year, segmented by the specified dimension.
- name: int_kpis__product_guest_agg_metrics
description:
This model aggregates multiple metrics on a Year-to-date, Month-to-date or
Week-to-date basis. This model changes the display format of the model
int_kpis__product_guest_daily_metrics pivoting the metrics columns and
adding a timeframe dimension.
columns:
- name: metric
data_type: text
description: Name of the business metric
- name: has_payment
data_type: string
description: Has there been any guest payments on the guest journey.
data_tests:
- not_null
- accepted_values:
values:
- W/O Payment
- With Payment
- name: has_id_check
data_type: string
description: Does the verification in the guest journey
includes Government Id Check for the bookings.
data_tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: timeframe
data_type: text
description: |
Timeframe considered for the aggregation, it could be Year-to-date,
Month-to-date or Week-to-date
data_tests:
- not_null
- accepted_values:
values:
- YTD
- MTD
- WTD
- name: current_value
data_type: numeric
description: |
Numeric value (integer or decimal) that corresponds to the timeframe
computation of the metric at the current date.
For example if the current date is 27/11/2024 and the timeframe is MTD,
then this value would correspond to the computation of the metric for
the dates between 01/11/2024 and 27/11/2024.
- name: py_value
data_type: numeric
description: |
Numeric value (integer or decimal) that corresponds to the timeframe
computation of the metric at the current date but on the previous year.
For example if the current date is 27/11/2024 and the timeframe is MTD,
then this value would correspond to the computation of the metric for
the dates between 01/11/2023 and 27/11/2023.
- name: pp_value
data_type: numeric
description: |
Numeric value (integer or decimal) that corresponds to the timeframe
computation of the metric at the current date but on the previous period.
For example if the current date is 27/11/2024 and the timeframe is MTD,
then this value would correspond to the computation of the metric for
the dates between 01/10/2024 and 27/10/2024.
- name: int_kpis__metric_daily_new_dash_created_services
description: |
This model computes the Daily Created Services at the deepest granularity.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services created after the user has moved to New Dash.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_booking,
- service_name
- service_business_type
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_booking
- service_name
- service_business_type
columns:
- name: date
data_type: date
description: Date of when Services have been created.
data_tests:
- not_null
- name: id_booking
data_type: bigint
description: Unique identifier of the Booking.
data_tests:
- not_null
- name: service_name
data_type: string
description: Name of the created service.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: is_upgraded_service
data_type: string
description: |
Whether the service is an upgraded version of the
default. In other words, if it's not Basic Screening.
data_tests:
- not_null
- accepted_values:
values:
- "YES"
- "NO"
- name: service_business_type
data_type: string
description: |
Identifies the service type (Screening, Deposit Management, Protection)
according to New Pricing documentation.
Cannot be null.
data_tests:
- not_null
- accepted_values:
values:
- "SCREENING"
- "PROTECTION"
- "DEPOSIT_MANAGEMENT"
- "UNKNOWN"
- "UNSET"
- name: new_dash_version
data_type: string
description: |
The version of the New Dash. It corresponds to the
release or migration phase from user point of view.
data_tests:
- not_null
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_services
data_type: bigint
description: |
Count of daily services created in a given date and per specified dimension.
- name: int_kpis__metric_monthly_new_dash_created_services
description: |
This model computes the Monthly Created Services at the
deepest granularity.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services created after the user has moved to New Dash.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- service_name,
- id_deal,
- active_accommodations_per_deal_segmentation,
- service_business_type.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- service_name
- id_deal
- active_accommodations_per_deal_segmentation
- service_business_type
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: service_name
data_type: string
description: Name of the created service.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: service_business_type
data_type: string
description: |
Identifies the service type (Screening, Deposit Management, Protection)
according to New Pricing documentation.
Cannot be null.
data_tests:
- not_null
- accepted_values:
values:
- "SCREENING"
- "PROTECTION"
- "DEPOSIT_MANAGEMENT"
- "UNKNOWN"
- "UNSET"
- name: is_upgraded_service
data_type: string
description: |
Whether the service is an upgraded version of the
default. In other words, if it's not Basic Screening.
data_tests:
- not_null
- accepted_values:
values:
- "YES"
- "NO"
- name: new_dash_version
data_type: string
description: |
The version of the New Dash. It corresponds to the
release or migration phase from user point of view.
data_tests:
- not_null
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_services
data_type: bigint
description: |
Count of services created in a given month and per specified dimension.
- name: booking_with_created_services_count
data_type: bigint
description: |
Count of unique bookings in a given month and per specified dimension.
This is an approximation to booking count since different services can
apply to the same booking and these do not need to be created in the same
time period. Therefore, it's not an additive metric.
- name: int_kpis__metric_weekly_new_dash_created_services
description: |
This model computes the Weekly Created Services at the
deepest granularity.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services created after the user has moved to New Dash.
Be aware that any dimension that can change over the weekly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- service_name,
- id_deal,
- active_accommodations_per_deal_segmentation,
- service_business_type.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- service_name
- id_deal
- active_accommodations_per_deal_segmentation
- service_business_type
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: service_name
data_type: string
description: Name of the created service.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: service_business_type
data_type: string
description: |
Identifies the service type (Screening, Deposit Management, Protection)
according to New Pricing documentation.
Cannot be null.
data_tests:
- not_null
- accepted_values:
values:
- "SCREENING"
- "PROTECTION"
- "DEPOSIT_MANAGEMENT"
- "UNKNOWN"
- "UNSET"
- name: is_upgraded_service
data_type: string
description: |
Whether the service is an upgraded version of the
default. In other words, if it's not Basic Screening.
data_tests:
- not_null
- accepted_values:
values:
- "YES"
- "NO"
- name: new_dash_version
data_type: string
description: |
The version of the New Dash. It corresponds to the
release or migration phase from user point of view.
data_tests:
- not_null
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: created_services
data_type: bigint
description: |
Count of services created in a given month and per specified dimension.
- name: booking_with_created_services_count
data_type: bigint
description: |
Count of unique bookings in a given month and per specified dimension.
This is an approximation to booking count since different services can
apply to the same booking and these do not need to be created in the same
time period. Therefore, it's not an additive metric.
- name: int_kpis__agg_weekly_new_dash_created_services
description: |
This model computes the dimension aggregation for Weekly Created Services.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services created after the user has moved to New Dash.
The primary key of this model is end_date, dimension and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- created_services
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_new_dash_version
- by_has_upgraded_service
- by_service
- by_service_business_type
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_services
data_type: bigint
description: The weekly created services for a given date range, dimension and value.
- name: booking_with_created_services_count
data_type: bigint
description: |
The weekly bookings with created services for a given date range, dimension and value.
This is an approximation to booking count since different services can
apply to the same booking and these do not need to be created in the same
time period. Therefore, it's not an additive metric.
- name: int_kpis__agg_monthly_new_dash_created_services
description: |
This model computes the dimension aggregation for Monthly Created Services.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services created after the user has moved to New Dash.
The primary key of this model is end_date, dimension and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- created_services
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_new_dash_version
- by_has_upgraded_service
- by_service
- by_service_business_type
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_services
data_type: bigint
description: The monthly created services for a given date range, dimension and value.
- name: booking_with_created_services_count
data_type: bigint
description: |
The monthly bookings with created services for a given date range, dimension and value.
This is an approximation to booking count since different services can
apply to the same booking and these do not need to be created in the same
time period. Therefore, it's not an additive metric.
- name: int_kpis__agg_daily_new_dash_created_services
description: |
This model computes the dimension aggregation for Daily Created Services.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services created after the user has moved to New Dash.
The primary key of this model is date, dimension and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- dimension
- dimension_value
columns:
- name: date
data_type: date
description: |
The daily date acting as time range for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- created_services
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_new_dash_version
- by_has_upgraded_service
- by_service
- by_service_business_type
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_services
data_type: bigint
description: The daily created services for a given date, dimension and value.
- name: booking_with_created_services_count
data_type: bigint
description: |
The daily bookings with created services for a given date, dimension and value.
This is an approximation to booking count since different services can
apply to the same booking and these do not need to be created in the same
time period. Therefore, it's not an additive metric.
- name: int_kpis__product_new_dash_agg_metrics
description: |
This model serves as the skeleton for New Dash metrics and dimensions.
This model computes the time granularity aggregation per previously computed
dimension aggregation.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- time_granularity
- dimension
- dimension_value
columns:
- name: date
data_type: date
description: |
The end date of the time range specified in the time_granularity
for the dimension, dimension_value and metrics in this record.
data_tests:
- not_null
- name: time_granularity
data_type: string
description: The time dimension.
data_tests:
- accepted_values:
values:
- daily
- weekly
- monthly
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_new_dash_version
- by_has_upgraded_service
- by_service
- by_service_business_type
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: created_services
data_type: bigint
description: |
The created services for a given time granularity, date or dates range,
dimension and value.
- name: booking_with_created_services_count
data_type: bigint
description: |
The bookings with created services for a given time granularity, date or
dates range, dimension and value.
This is an approximation to booking count since different services can
apply to the same booking and these do not need to be created in the same
time period. Therefore, it's not an additive metric.
- name: total_chargeable_services
data_type: integer
description: |
The total chargeable services for a given time granularity, date or
dates range, dimension and value.
- name: total_chargeable_amount_in_gbp
data_type: decimal
description: |
The total daily chargeable amount for a given time granularity, date or
dates range, dimension and value, in GBP.
- name: unique_chargeable_bookings
data_type: integer
description: |
The unique daily chargeable bookings for a given time granularity, date or
dates range, dimension and value.
This metric is not additive, and its value can vary depending on the time
period considered.
- name: unique_chargeable_listings
data_type: integer
description: |
The unique daily chargeable accommodations, or listings, for a given time
granularity, date or dates range, dimension and value.
This metric is not additive, and its value can vary depending on the time
period considered.
- name: int_kpis__metric_daily_new_dash_chargeable_services
description: |
This model computes the Daily Chargeable Services at the deepest granularity.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services chargeable after the user has moved to New Dash.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_booking,
- service_name
- service_business_type
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_booking
- service_name
- service_business_type
columns:
- name: date
data_type: date
description: Date of when Services are supposed to be charged.
data_tests:
- not_null
- name: id_booking
data_type: bigint
description: Unique identifier of the Booking.
data_tests:
- not_null
- name: service_name
data_type: string
description: Name of the chargeable service.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: id_accommodation
data_type: bigint
description: Unique identifier of an accommodation, or listing.
data_tests:
- not_null
- name: is_upgraded_service
data_type: string
description: |
Whether the service is an upgraded version of the
default. In other words, if it's not Basic Screening.
data_tests:
- not_null
- accepted_values:
values:
- "YES"
- "NO"
- name: service_business_type
data_type: string
description: |
Identifies the service type (Screening, Deposit Management, Protection)
according to New Pricing documentation.
Cannot be null.
data_tests:
- not_null
- accepted_values:
values:
- "SCREENING"
- "PROTECTION"
- "DEPOSIT_MANAGEMENT"
- "UNKNOWN"
- "UNSET"
- name: new_dash_version
data_type: string
description: |
The version of the New Dash. It corresponds to the
release or migration phase from user point of view.
data_tests:
- not_null
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: chargeable_services
data_type: integer
description: |
Count of daily chargeable services in a given date and per specified
dimension.
- name: service_total_price_in_gbp
data_type: decimal
description: |
Sum of the total prices of the chargeable services in a given date and
per specified dimension, in GBP.
- name: int_kpis__metric_monthly_new_dash_chargeable_services
description: |
This model computes the Monthly Chargeable Services at the
deepest granularity.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services chargeable after the user has moved to New Dash.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- service_name,
- id_booking,
- active_accommodations_per_deal_segmentation.
- service_business_type
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_booking
- service_name
- active_accommodations_per_deal_segmentation
- service_business_type
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_booking
data_type: bigint
description: Unique identifier of the Booking.
data_tests:
- not_null
- name: service_name
data_type: string
description: Name of the chargeable service.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: id_accommodation
data_type: bigint
description: Unique identifier of an accommodation, or listing.
data_tests:
- not_null
- name: is_upgraded_service
data_type: string
description: |
Whether the service is an upgraded version of the
default. In other words, if it's not Basic Screening.
data_tests:
- not_null
- accepted_values:
values:
- "YES"
- "NO"
- name: service_business_type
data_type: string
description: |
Identifies the service type (Screening, Deposit Management, Protection)
according to New Pricing documentation.
Cannot be null.
data_tests:
- not_null
- accepted_values:
values:
- "SCREENING"
- "PROTECTION"
- "DEPOSIT_MANAGEMENT"
- "UNKNOWN"
- "UNSET"
- name: new_dash_version
data_type: string
description: |
The version of the New Dash. It corresponds to the
release or migration phase from user point of view.
data_tests:
- not_null
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: chargeable_services
data_type: integer
description: |
Count of monthly chargeable services in a given date and per specified
dimension.
- name: service_total_price_in_gbp
data_type: decimal
description: |
Sum of the total prices of the chargeable services in a given time range
and per specified dimension, in GBP.
- name: int_kpis__metric_weekly_new_dash_chargeable_services
description: |
This model computes the Weekly Chargeable Services at the
deepest granularity.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services chargeable after the user has moved to New Dash.
Be aware that any dimension that can change over the monthly period,
such as daily segmentations, are included in the primary key of the
model.
The unique key corresponds to:
- end_date,
- service_name,
- id_booking,
- active_accommodations_per_deal_segmentation,
- service_business_type
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_booking
- service_name
- active_accommodations_per_deal_segmentation
- service_business_type
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: id_booking
data_type: bigint
description: Unique identifier of the Booking.
data_tests:
- not_null
- name: service_name
data_type: string
description: Name of the chargeable service.
data_tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
data_tests:
- not_null
- name: id_accommodation
data_type: bigint
description: Unique identifier of an accommodation, or listing.
data_tests:
- not_null
- name: is_upgraded_service
data_type: string
description: |
Whether the service is an upgraded version of the
default. In other words, if it's not Basic Screening.
data_tests:
- not_null
- accepted_values:
values:
- "YES"
- "NO"
- name: service_business_type
data_type: string
description: |
Identifies the service type (Screening, Deposit Management, Protection)
according to New Pricing documentation.
Cannot be null.
data_tests:
- not_null
- accepted_values:
values:
- "SCREENING"
- "PROTECTION"
- "DEPOSIT_MANAGEMENT"
- "UNKNOWN"
- "UNSET"
- name: new_dash_version
data_type: string
description: |
The version of the New Dash. It corresponds to the
release or migration phase from user point of view.
data_tests:
- not_null
- name: active_accommodations_per_deal_segmentation
data_type: string
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
data_tests:
- not_null
- accepted_values:
values:
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
- name: main_billing_country_iso_3_per_deal
data_type: string
description: |
Main billing country of the host aggregated at Deal level.
data_tests:
- not_null
- name: chargeable_services
data_type: integer
description: |
Count of weekly chargeable services in a given date and per specified
dimension.
- name: service_total_price_in_gbp
data_type: decimal
description: |
Sum of the total prices of the chargeable services in a given time range
and per specified dimension, in GBP.
- name: int_kpis__agg_weekly_new_dash_chargeable_services
description: |
This model computes the dimension aggregation for Weekly Chargeable Services.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services chargeable after the user has moved to New Dash.
The primary key of this model is end_date, dimension and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- total_chargeable_services
- total_chargeable_amount_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_new_dash_version
- by_has_upgraded_service
- by_service
- by_service_business_type
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: total_chargeable_services
data_type: integer
description: |
The total weekly chargeable services in a given time range and per specified
dimension.
- name: total_chargeable_amount_in_gbp
data_type: decimal
description: |
The total weekly chargeable amount in a given time range and per specified
dimension, in GBP.
- name: unique_chargeable_bookings
data_type: integer
description: |
The unique weekly chargeable bookings in a given time range and per specified
dimension. This metric is not additive, and its value can vary depending
on the time period considered.
- name: unique_chargeable_listings
data_type: integer
description: |
The unique weekly chargeable accommodations, or listings, in a given time range
and per specified dimension. This metric is not additive, and its value
can vary depending on the time period considered.
- name: int_kpis__agg_monthly_new_dash_chargeable_services
description: |
This model computes the dimension aggregation for Monthly Chargeable Services.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services chargeable after the user has moved to New Dash.
The primary key of this model is end_date, dimension and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- total_chargeable_services
- total_chargeable_amount_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_new_dash_version
- by_has_upgraded_service
- by_service
- by_service_business_type
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: total_chargeable_services
data_type: integer
description: |
The total monthly chargeable services in a given time range and per specified
dimension.
- name: total_chargeable_amount_in_gbp
data_type: decimal
description: |
The total monthly chargeable amount in a given time range and per specified
dimension, in GBP.
- name: unique_chargeable_bookings
data_type: integer
description: |
The unique monthly chargeable bookings in a given time range and per specified
dimension. This metric is not additive, and its value can vary depending
on the time period considered.
- name: unique_chargeable_listings
data_type: integer
description: |
The unique monthly chargeable accommodations, or listings, in a given time range
and per specified dimension. This metric is not additive, and its value
can vary depending on the time period considered.
- name: int_kpis__agg_daily_new_dash_chargeable_services
description: |
This model computes the dimension aggregation for Daily Chargeable Services.
It only retrieves services that come from users that are in New Dash, as well
as it only considers services chargeable after the user has moved to New Dash.
The primary key of this model is date, dimension and dimension_value.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- dimension
- dimension_value
columns:
- name: date
data_type: date
description: |
The daily date acting as time range for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- total_chargeable_services
- total_chargeable_amount_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- by_new_dash_version
- by_has_upgraded_service
- by_service
- by_service_business_type
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: total_chargeable_services
data_type: integer
description: |
The total daily chargeable services in a given time range and per specified
dimension.
- name: total_chargeable_amount_in_gbp
data_type: decimal
description: |
The total daily chargeable amount in a given time range and per specified
dimension, in GBP.
- name: unique_chargeable_bookings
data_type: integer
description: |
The unique daily chargeable bookings in a given time range and per specified
dimension. This metric is not additive, and its value can vary depending
on the time period considered.
- name: unique_chargeable_listings
data_type: integer
description: |
The unique daily chargeable accommodations, or listings, in a given time range
and per specified dimension. This metric is not additive, and its value
can vary depending on the time period considered.
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