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data-dwh-dbt-project/models/intermediate/kpis/schema.yml

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Merged PR 3329: First version of KPIs refactored - created bookings # Description Creates skeleton for new KPIs data flow for created_bookings metric. Details are accessible [here](https://www.notion.so/knowyourguest-superhog/KPIs-Refactor-Let-s-go-daily-2024-10-23-1280446ff9c980dc87a3dc7453e95f06?pvs=4#12a0446ff9c98085bf4dfc77f6fc22f7) In essence: * Models are created in intermediate in a kpis folder. * Models have a daily segmentation. This includes `created_bookings` models, but also the daily lifecycle per listing and the segmentation. It also adds a `dimension_dates` model specific for KPIs. These have all the dimensions already in place and handle all the crazy logic. * Other time aggregation models simply read from existing daily models which are much easier (`int_kpis__metric_mtd_created_bookings` and `int_kpis__metric_monthly_created_bookings`). * Dimensionality aggregation can be easily added within a given timeframe (daily, mtd, monthly). For instance, I do it for mtd in the `int_kpis__aggregated_mtd_created_bookings` and for monthly in `int_kpis__aggregated_monthly_created_bookings` * Macro configuration for dimensions: Allows to set any specific dimension for `aggregated` models. By default, the subset of global, by billing country, by number of listings and by deal apply - since these are needed for Main KPIs. I added an example with Dash Source, that currently does not exist and it's currently configured as only appearing for created bookings. * Testing `aggregated` models completeness. A new macro called `assert_dimension_completeness` is available that ensures additive metrics are consistent vs. the global result, configurable at schema level. * Testing refactor impact. I'm aware that changing the lifecycle model to daily impacts the volumes for listing segments. For the rest, I added a `tmp` test that checks that the dimension and dimension value per date exactly match comparing new vs. old computation. Latest edits: * Changed naming convention * Split of MTD and Monthly. Now these are 2 different entities, as stated in `int_kpis__dimension_dates`. * Added start_date and end_date for models that contemplate a range (mtd, monthly). * Added a small readme entry in the kpis folders. Mostly it states nomenclature and some first conventions. Dbt docs: ![image (5).png](https://guardhog.visualstudio.com/4148d95f-4b6d-4205-bcff-e9c8e0d2ca65/_apis/git/repositories/54ac356f-aad7-46d2-b62c-e8c5b3bb8ebf/pullRequests/3329/attachments/image%20%285%29.png) # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [ ] I have checked for DRY opportunities with other models and docs. **Likely we'll be able to add macros for mtd and dim_agg models. We will see later on.** - [ ] I've picked the right materialization for the affected models. **Models run ok except for the daily lifecycle of listings, which lasts several minutes in the first run. Model curr...
2024-10-30 08:55:19 +00:00
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.
tests:
- unique
- not_null
- name: year
data_type: int
description: Year number of the given date.
tests:
- not_null
- name: month
data_type: int
description: Month number of the given date.
tests:
- not_null
- name: day
data_type: int
description: Day monthly number of the given date.
tests:
- not_null
- name: first_day_month
data_type: date
description: |
First day of the month correspoding to the date field.
tests:
- not_null
- name: last_day_month
data_type: date
description: |
Last day of the month correspoding to the date field.
tests:
- not_null
- name: is_end_of_month
data_type: boolean
description: True if it's end of month, false otherwise.
tests:
- not_null
- name: is_current_month
data_type: boolean
description: |
True if the date is within the current month, false otherwise.
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.
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.
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.
tests:
- not_null
- name: id_accommodation
data_type: bigint
description: Id of the accommodation or listing.
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.
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__dimension_daily_accommodation
description: |
This model computes the deal segmentation per number of
listings in a daily manner.
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.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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,
- dash_source.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
- dash_source
columns:
- name: date
data_type: date
description: Date of when Bookings have been created.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
tests:
- not_null
- name: dash_source
data_type: string
description: Dashboard source, either old or new.
tests:
- not_null
- accepted_values:
values:
- "New Dash"
- "Old Dash"
- 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.
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.
tests:
- not_null
- name: created_bookings
data_type: bigint
description: |
Count of daily bookings created in a given date and per specified dimension.
- 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,
- dash_source,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- dash_source
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
tests:
- not_null
- name: dash_source
data_type: string
description: Dashboard source, either old or new.
tests:
- not_null
- accepted_values:
values:
- "New Dash"
- "Old Dash"
- 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.
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.
tests:
- not_null
- name: created_bookings
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated bookings created in a given month
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
and per specified dimension.
Merged PR 3329: First version of KPIs refactored - created bookings # Description Creates skeleton for new KPIs data flow for created_bookings metric. Details are accessible [here](https://www.notion.so/knowyourguest-superhog/KPIs-Refactor-Let-s-go-daily-2024-10-23-1280446ff9c980dc87a3dc7453e95f06?pvs=4#12a0446ff9c98085bf4dfc77f6fc22f7) In essence: * Models are created in intermediate in a kpis folder. * Models have a daily segmentation. This includes `created_bookings` models, but also the daily lifecycle per listing and the segmentation. It also adds a `dimension_dates` model specific for KPIs. These have all the dimensions already in place and handle all the crazy logic. * Other time aggregation models simply read from existing daily models which are much easier (`int_kpis__metric_mtd_created_bookings` and `int_kpis__metric_monthly_created_bookings`). * Dimensionality aggregation can be easily added within a given timeframe (daily, mtd, monthly). For instance, I do it for mtd in the `int_kpis__aggregated_mtd_created_bookings` and for monthly in `int_kpis__aggregated_monthly_created_bookings` * Macro configuration for dimensions: Allows to set any specific dimension for `aggregated` models. By default, the subset of global, by billing country, by number of listings and by deal apply - since these are needed for Main KPIs. I added an example with Dash Source, that currently does not exist and it's currently configured as only appearing for created bookings. * Testing `aggregated` models completeness. A new macro called `assert_dimension_completeness` is available that ensures additive metrics are consistent vs. the global result, configurable at schema level. * Testing refactor impact. I'm aware that changing the lifecycle model to daily impacts the volumes for listing segments. For the rest, I added a `tmp` test that checks that the dimension and dimension value per date exactly match comparing new vs. old computation. Latest edits: * Changed naming convention * Split of MTD and Monthly. Now these are 2 different entities, as stated in `int_kpis__dimension_dates`. * Added start_date and end_date for models that contemplate a range (mtd, monthly). * Added a small readme entry in the kpis folders. Mostly it states nomenclature and some first conventions. Dbt docs: ![image (5).png](https://guardhog.visualstudio.com/4148d95f-4b6d-4205-bcff-e9c8e0d2ca65/_apis/git/repositories/54ac356f-aad7-46d2-b62c-e8c5b3bb8ebf/pullRequests/3329/attachments/image%20%285%29.png) # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [ ] I have checked for DRY opportunities with other models and docs. **Likely we'll be able to add macros for mtd and dim_agg models. We will see later on.** - [ ] I've picked the right materialization for the affected models. **Models run ok except for the daily lifecycle of listings, which lasts several minutes in the first run. Model curr...
2024-10-30 08:55:19 +00:00
- 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,
- dash_source,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- dash_source
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
tests:
- not_null
- name: dash_source
data_type: string
description: Dashboard source, either old or new.
tests:
- not_null
- accepted_values:
values:
- "New Dash"
- "Old Dash"
- 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.
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.
tests:
- not_null
- name: created_bookings
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated bookings created in a given month up to the
Merged PR 3329: First version of KPIs refactored - created bookings # Description Creates skeleton for new KPIs data flow for created_bookings metric. Details are accessible [here](https://www.notion.so/knowyourguest-superhog/KPIs-Refactor-Let-s-go-daily-2024-10-23-1280446ff9c980dc87a3dc7453e95f06?pvs=4#12a0446ff9c98085bf4dfc77f6fc22f7) In essence: * Models are created in intermediate in a kpis folder. * Models have a daily segmentation. This includes `created_bookings` models, but also the daily lifecycle per listing and the segmentation. It also adds a `dimension_dates` model specific for KPIs. These have all the dimensions already in place and handle all the crazy logic. * Other time aggregation models simply read from existing daily models which are much easier (`int_kpis__metric_mtd_created_bookings` and `int_kpis__metric_monthly_created_bookings`). * Dimensionality aggregation can be easily added within a given timeframe (daily, mtd, monthly). For instance, I do it for mtd in the `int_kpis__aggregated_mtd_created_bookings` and for monthly in `int_kpis__aggregated_monthly_created_bookings` * Macro configuration for dimensions: Allows to set any specific dimension for `aggregated` models. By default, the subset of global, by billing country, by number of listings and by deal apply - since these are needed for Main KPIs. I added an example with Dash Source, that currently does not exist and it's currently configured as only appearing for created bookings. * Testing `aggregated` models completeness. A new macro called `assert_dimension_completeness` is available that ensures additive metrics are consistent vs. the global result, configurable at schema level. * Testing refactor impact. I'm aware that changing the lifecycle model to daily impacts the volumes for listing segments. For the rest, I added a `tmp` test that checks that the dimension and dimension value per date exactly match comparing new vs. old computation. Latest edits: * Changed naming convention * Split of MTD and Monthly. Now these are 2 different entities, as stated in `int_kpis__dimension_dates`. * Added start_date and end_date for models that contemplate a range (mtd, monthly). * Added a small readme entry in the kpis folders. Mostly it states nomenclature and some first conventions. Dbt docs: ![image (5).png](https://guardhog.visualstudio.com/4148d95f-4b6d-4205-bcff-e9c8e0d2ca65/_apis/git/repositories/54ac356f-aad7-46d2-b62c-e8c5b3bb8ebf/pullRequests/3329/attachments/image%20%285%29.png) # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [ ] I have checked for DRY opportunities with other models and docs. **Likely we'll be able to add macros for mtd and dim_agg models. We will see later on.** - [ ] I've picked the right materialization for the affected models. **Models run ok except for the daily lifecycle of listings, which lasts several minutes in the first run. Model curr...
2024-10-30 08:55:19 +00:00
given date and per specified dimension.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
Addressed comments
2024-11-04 14:29:26 +01:00
metric_column_name: created_bookings
Merged PR 3329: First version of KPIs refactored - created bookings # Description Creates skeleton for new KPIs data flow for created_bookings metric. Details are accessible [here](https://www.notion.so/knowyourguest-superhog/KPIs-Refactor-Let-s-go-daily-2024-10-23-1280446ff9c980dc87a3dc7453e95f06?pvs=4#12a0446ff9c98085bf4dfc77f6fc22f7) In essence: * Models are created in intermediate in a kpis folder. * Models have a daily segmentation. This includes `created_bookings` models, but also the daily lifecycle per listing and the segmentation. It also adds a `dimension_dates` model specific for KPIs. These have all the dimensions already in place and handle all the crazy logic. * Other time aggregation models simply read from existing daily models which are much easier (`int_kpis__metric_mtd_created_bookings` and `int_kpis__metric_monthly_created_bookings`). * Dimensionality aggregation can be easily added within a given timeframe (daily, mtd, monthly). For instance, I do it for mtd in the `int_kpis__aggregated_mtd_created_bookings` and for monthly in `int_kpis__aggregated_monthly_created_bookings` * Macro configuration for dimensions: Allows to set any specific dimension for `aggregated` models. By default, the subset of global, by billing country, by number of listings and by deal apply - since these are needed for Main KPIs. I added an example with Dash Source, that currently does not exist and it's currently configured as only appearing for created bookings. * Testing `aggregated` models completeness. A new macro called `assert_dimension_completeness` is available that ensures additive metrics are consistent vs. the global result, configurable at schema level. * Testing refactor impact. I'm aware that changing the lifecycle model to daily impacts the volumes for listing segments. For the rest, I added a `tmp` test that checks that the dimension and dimension value per date exactly match comparing new vs. old computation. Latest edits: * Changed naming convention * Split of MTD and Monthly. Now these are 2 different entities, as stated in `int_kpis__dimension_dates`. * Added start_date and end_date for models that contemplate a range (mtd, monthly). * Added a small readme entry in the kpis folders. Mostly it states nomenclature and some first conventions. Dbt docs: ![image (5).png](https://guardhog.visualstudio.com/4148d95f-4b6d-4205-bcff-e9c8e0d2ca65/_apis/git/repositories/54ac356f-aad7-46d2-b62c-e8c5b3bb8ebf/pullRequests/3329/attachments/image%20%285%29.png) # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [ ] I have checked for DRY opportunities with other models and docs. **Likely we'll be able to add macros for mtd and dim_agg models. We will see later on.** - [ ] I've picked the right materialization for the affected models. **Models run ok except for the daily lifecycle of listings, which lasts several minutes in the first run. Model curr...
2024-10-30 08:55:19 +00:00
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_dash_source
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
tests:
- not_null
- name: created_bookings
data_type: bigint
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
description: The monthly created bookings for a given date, dimension and value.
Merged PR 3329: First version of KPIs refactored - created bookings # Description Creates skeleton for new KPIs data flow for created_bookings metric. Details are accessible [here](https://www.notion.so/knowyourguest-superhog/KPIs-Refactor-Let-s-go-daily-2024-10-23-1280446ff9c980dc87a3dc7453e95f06?pvs=4#12a0446ff9c98085bf4dfc77f6fc22f7) In essence: * Models are created in intermediate in a kpis folder. * Models have a daily segmentation. This includes `created_bookings` models, but also the daily lifecycle per listing and the segmentation. It also adds a `dimension_dates` model specific for KPIs. These have all the dimensions already in place and handle all the crazy logic. * Other time aggregation models simply read from existing daily models which are much easier (`int_kpis__metric_mtd_created_bookings` and `int_kpis__metric_monthly_created_bookings`). * Dimensionality aggregation can be easily added within a given timeframe (daily, mtd, monthly). For instance, I do it for mtd in the `int_kpis__aggregated_mtd_created_bookings` and for monthly in `int_kpis__aggregated_monthly_created_bookings` * Macro configuration for dimensions: Allows to set any specific dimension for `aggregated` models. By default, the subset of global, by billing country, by number of listings and by deal apply - since these are needed for Main KPIs. I added an example with Dash Source, that currently does not exist and it's currently configured as only appearing for created bookings. * Testing `aggregated` models completeness. A new macro called `assert_dimension_completeness` is available that ensures additive metrics are consistent vs. the global result, configurable at schema level. * Testing refactor impact. I'm aware that changing the lifecycle model to daily impacts the volumes for listing segments. For the rest, I added a `tmp` test that checks that the dimension and dimension value per date exactly match comparing new vs. old computation. Latest edits: * Changed naming convention * Split of MTD and Monthly. Now these are 2 different entities, as stated in `int_kpis__dimension_dates`. * Added start_date and end_date for models that contemplate a range (mtd, monthly). * Added a small readme entry in the kpis folders. Mostly it states nomenclature and some first conventions. Dbt docs: ![image (5).png](https://guardhog.visualstudio.com/4148d95f-4b6d-4205-bcff-e9c8e0d2ca65/_apis/git/repositories/54ac356f-aad7-46d2-b62c-e8c5b3bb8ebf/pullRequests/3329/attachments/image%20%285%29.png) # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [ ] I have checked for DRY opportunities with other models and docs. **Likely we'll be able to add macros for mtd and dim_agg models. We will see later on.** - [ ] I've picked the right materialization for the affected models. **Models run ok except for the daily lifecycle of listings, which lasts several minutes in the first run. Model curr...
2024-10-30 08:55:19 +00:00
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: created_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_dash_source
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
tests:
- not_null
- name: created_bookings
data_type: bigint
description: The month-to-date created bookings for a given date, dimension and value.
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
- 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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been created.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys created in a given month
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys created in a given month up to the
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
given date and per specified dimension.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: created_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
tests:
- not_null
- name: created_guest_journeys
data_type: bigint
description: The monthtly created guest journeys for a given date, dimension and value.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: created_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been started.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: started_guest_journeys
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys started in a given month
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: started_guest_journeys
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys started in a given month up to the
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
given date and per specified dimension.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: started_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: started_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been completed.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: completed_guest_journeys
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys completed in a given month
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: completed_guest_journeys
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys completed in a given month up to the
Merged PR 3377: Adds GJ Created, Started and Completed in new KPIs flow # Description Adds GJ Created, Started and Completed. Each model has: * A Daily model * A Monthly/MTD without dimension aggregate * A Monthly/MTD with dimension aggregate * A comparison vs. the current flow of KPIs in the form of a test It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good. I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022. This does not include: * Guest Journeys with Payment. I'll do this in a separated PR * Guest Payments/Revenue. I'll do this in a separated PR # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being** - [X] I've picked the right materialization for the affected models. **Runs quite fast** # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 11:45:45 +00:00
given date and per specified dimension.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: completed_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: completed_guest_journeys
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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.
Merged PR 3385: Adds Guest Journey with Payment metric # Description Adds GJ with Payment. It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 16:43:50 +00:00
- 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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been completed.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: guest_journeys_with_payment
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys completed in a given month
Merged PR 3385: Adds Guest Journey with Payment metric # Description Adds GJ with Payment. It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 16:43:50 +00:00
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: guest_journeys_with_payment
data_type: bigint
description: |
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
Count of accumulated guest journeys completed in a given month up to the
Merged PR 3385: Adds Guest Journey with Payment metric # Description Adds GJ with Payment. It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-30 16:43:50 +00:00
given date and per specified dimension.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: guest_journeys_with_payment
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: guest_journeys_with_payment
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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.
Merged PR 3387: Adds Guest Payments metrics # Description Adds Guest Payments metrics, namely: * deposit_fees_in_gbp * waiver_payments_in_gbp * checkin_cover_fees_in_gbp * total_guest_payments_in_gbp It includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23453
2024-10-31 09:03:15 +00:00
- 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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Guest Journeys have been completed.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: deposit_fees_in_gbp
- assert_dimension_completeness:
metric_column_name: waiver_payments_in_gbp
- assert_dimension_completeness:
metric_column_name: checkin_cover_fees_in_gbp
- assert_dimension_completeness:
metric_column_name: total_guest_payments_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: deposit_fees_in_gbp
- assert_dimension_completeness:
metric_column_name: waiver_payments_in_gbp
- assert_dimension_completeness:
metric_column_name: checkin_cover_fees_in_gbp
- assert_dimension_completeness:
metric_column_name: total_guest_payments_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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.
Merged PR 3391: Adds Check-Out, Cancelled and Billable Bookings # Description Adds Check-Out, Cancelled and Billable Bookings in the new KPI flow. For each of these metrics, it includes: * Daily model * Monthly/MTD without dimension aggregates * Monthly/MTD with dimension aggregates * Schema entries for the abovementioned 5 models * Temporary test to compare the different metrics against current production KPIs I also implemented a quick performance fix that removes the dependency of Billable Bookings from Booking Charge Events, since Bookings table already contains the needed information. # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23454
2024-10-31 14:31:19 +00:00
- 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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Bookings have been checked-out.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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: 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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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: 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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: check_out_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
tests:
- not_null
- name: check_out_bookings
data_type: bigint
description: The monthly checked-out bookings for a given date, dimension and value.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: check_out_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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: 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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Bookings have been billable.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: billable_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
tests:
- not_null
- name: billable_bookings
data_type: bigint
description: The monthly billable bookings for a given date, dimension and value.
- name: int_kpis__aggregated_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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: billable_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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_cancelled_bookings
description: |
This model computes the Daily Cancelled Bookings at the deepest granularity.
The unique key corresponds to the deepest granularity of the model,
in this case:
- date,
- id_deal.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Bookings have been cancelled.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: cancelled_bookings
data_type: bigint
description: |
Count of daily bookings cancelled in a given date and per specified dimension.
- name: int_kpis__metric_monthly_cancelled_bookings
description: |
This model computes the Monthly Cancelled 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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: cancelled_bookings
data_type: bigint
description: |
Count of accumulated bookings cancelled in a given month
and per specified dimension.
- name: int_kpis__metric_mtd_cancelled_bookings
description: |
This model computes the Month-To-Date Cancelled 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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
tests:
- not_null
- name: cancelled_bookings
data_type: bigint
description: |
Count of accumulated bookings cancelled in a given month up to the
given date and per specified dimension.
- name: int_kpis__aggregated_monthly_cancelled_bookings
description: |
This model computes the dimension aggregation for
Monthly Cancelled Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: cancelled_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
tests:
- not_null
- name: cancelled_bookings
data_type: bigint
description: The monthly cancelled bookings for a given date, dimension and value.
- name: int_kpis__aggregated_mtd_cancelled_bookings
description: |
This model computes the dimension aggregation for
Month-To-Date Cancelled Bookings.
The primary key of this model is end_date, dimension
and dimension_value.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: cancelled_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
tests:
- not_null
- name: cancelled_bookings
data_type: bigint
description: The month-to-date cancelled bookings for a given date, dimension and value.
Created models for new guest kpis
2024-10-31 11:44:26 +01:00
Fixed names
2024-11-04 15:28:31 +01:00
- name: int_kpis__metric_daily_check_in_attributed_guest_journeys
Created models for new guest kpis
2024-10-31 11:44:26 +01:00
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.
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.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
tests:
- not_null
- name: has_payment
Fixed names
2024-11-04 15:28:31 +01:00
data_type: string
description: Has there been any guest payments on the guest journey.
tests:
- not_null
- accepted_values:
values:
- W/O Payment
- With Payment
Created models for new guest kpis
2024-10-31 11:44:26 +01:00
- name: has_id_check
Fixed names
2024-11-04 15:28:31 +01:00
data_type: string
description: Does the verification in the guest journey
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
includes Government Id Check for the bookings.
Fixed names
2024-11-04 15:28:31 +01:00
tests:
- not_null
- accepted_values:
values:
- W/O Id Check
- With Id Check
Created models for new guest kpis
2024-10-31 11:44:26 +01:00
- 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.
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.
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.
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
CSAT score
2024-11-04 16:51:24 +01:00
- 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.
Fixed names
2024-11-04 15:28:31 +01:00
- name: int_kpis__metric_monthly_check_in_attributed_guest_journeys
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
description: |
This model computes the Monthly metrics associated with Guest Journeys
attributed to Check-In date at the deepest granularity.
The unique key corresponds to:
- end_date,
- id_deal,
- has_payment,
- has_id_check,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- has_payment
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: character varying
description: Unique identifier of an account.
tests:
- not_null
- name: has_payment
Fixed names
2024-11-04 15:28:31 +01:00
data_type: string
description: Has there been any guest payments on the guest journey.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
Fixed names
2024-11-04 15:28:31 +01:00
- accepted_values:
values:
- W/O Payment
- With Payment
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: has_id_check
Fixed names
2024-11-04 15:28:31 +01:00
data_type: string
description: Does the verification in the guest journey
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
include Government Id Check for the bookings.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
Fixed names
2024-11-04 15:28:31 +01:00
- accepted_values:
values:
- W/O Id Check
- With Id Check
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: active_accommodations_per_deal_segmentation
data_type: text
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
tests:
- not_null
- accepted_values:
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
values:
Addressed comments
2024-11-04 14:29:26 +01:00
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: main_billing_country_iso_3_per_deal
data_type: character varying
description: |
Main billing country of the host aggregated at Deal level.
tests:
- not_null
- name: created_guest_journeys_not_cancelled
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated count of daily guest journeys created, excluding cancelled
Addressed comments
2024-11-04 18:15:13 +01:00
bookings, in a given date and per specified dimension.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
- name: started_guest_journeys_not_cancelled
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated count of daily guest journeys started, excluding cancelled
Addressed comments
2024-11-04 18:15:13 +01:00
bookings, in a given date and per specified dimension.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
- name: completed_guest_journeys_not_cancelled
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated count of daily guest journeys completed, excluding cancelled
Addressed comments
2024-11-04 18:15:13 +01:00
bookings, in a given date and per specified dimension.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
- name: created_guest_journeys
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated count of daily guest journeys created in a given date and
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
per specified dimension.
tests:
- not_null
- name: started_guest_journeys
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated count of daily guest journeys started in a given date and
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
per specified dimension.
tests:
- not_null
- name: completed_guest_journeys
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated count of daily guest journeys completed in a given date and
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
per specified dimension.
tests:
- not_null
CSAT score
2024-11-04 16:51:24 +01:00
- name: count_csat_score
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated count of guest journeys with CSAT
(customer satisfaction score) in a given date, dimension, and value.
CSAT score
2024-11-04 16:51:24 +01:00
- name: average_csat_score
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Monthly accumulated average CSAT score in a given date, dimension, and value.
CSAT score
2024-11-04 16:51:24 +01:00
tests:
- dbt_expectations.expect_column_values_to_be_between:
min_value: 0
max_value: 5
strictly: false
Fixed names
2024-11-04 15:28:31 +01:00
- name: int_kpis__agg_monthly_check_in_attributed_guest_journeys
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
description: |
This model computes the dimension aggregation for Monthly metrics associated
to Guest Journeys attributed to Check-In date.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: text
description: |
The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
Addressed comments
2024-11-04 14:29:26 +01:00
metric_column_name: created_guest_journeys_not_cancelled
- assert_dimension_completeness:
metric_column_name: started_guest_journeys_not_cancelled
- assert_dimension_completeness:
metric_column_name: completed_guest_journeys_not_cancelled
- assert_dimension_completeness:
metric_column_name: created_guest_journeys
- assert_dimension_completeness:
metric_column_name: started_guest_journeys
- assert_dimension_completeness:
metric_column_name: completed_guest_journeys
CSAT score
2024-11-04 16:51:24 +01:00
- assert_dimension_completeness:
metric_column_name: count_csat_score
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- accepted_values:
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
values:
Addressed comments
2024-11-04 14:29:26 +01:00
- global
- by_deal
- by_has_payment
- by_has_id_check
- by_billing_country
- by_number_of_listings
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: dimension_value
data_type: text
description: |
The value or segment available for the selected dimension.
tests:
- not_null
- name: created_guest_journeys_not_cancelled
data_type: numeric
description: |
Monthly aggregated count of guest journeys created, excluding
cancelled bookings, for a given date, dimension, and value.
tests:
- not_null
- name: started_guest_journeys_not_cancelled
data_type: numeric
description: |
Monthly aggregated count of guest journeys started, excluding
cancelled bookings, for a given date, dimension, and value.
tests:
- not_null
- name: completed_guest_journeys_not_cancelled
data_type: numeric
description: |
Monthly aggregated count of guest journeys completed, excluding
cancelled bookings, for a given date, dimension, and value.
tests:
- not_null
- name: created_guest_journeys
data_type: numeric
description: |
Monthly aggregated count of guest journeys created for a given date,
dimension, and value.
tests:
- not_null
- name: started_guest_journeys
data_type: numeric
description: |
Monthly aggregated count of guest journeys started for a given date,
dimension, and value.
tests:
- not_null
- name: completed_guest_journeys
data_type: numeric
description: |
Monthly aggregated count of guest journeys completed for a given date,
dimension, and value.
tests:
- not_null
CSAT score
2024-11-04 16:51:24 +01:00
- name: count_csat_score
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Monthly aggregated count of guest journeys with CSAT
(customer satisfaction score) in a given date, dimension, and value.
CSAT score
2024-11-04 16:51:24 +01:00
- name: average_csat_score
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Monthly aggregated average CSAT score in a given date,
dimension, and value.
CSAT score
2024-11-04 16:51:24 +01:00
tests:
- dbt_expectations.expect_column_values_to_be_between:
min_value: 0
max_value: 5
strictly: false
Fixed names
2024-11-04 15:28:31 +01:00
- name: int_kpis__metric_mtd_check_in_attributed_guest_journeys
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
description: |
This model computes the Month-To-Date metrics associated with Guest Journeys
attributed to Check-In date at the deepest granularity.
The unique key corresponds to:
- end_date,
- id_deal,
- has_payment,
- has_id_check,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- has_payment
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: character varying
description: Unique identifier of an account.
tests:
- not_null
- name: has_payment
Fixed names
2024-11-04 15:28:31 +01:00
data_type: string
description: Has there been any guest payments on the guest journey.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
Fixed names
2024-11-04 15:28:31 +01:00
- accepted_values:
values:
- W/O Payment
- With Payment
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: has_id_check
Fixed names
2024-11-04 15:28:31 +01:00
data_type: string
description: Does the verification in the guest journey
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
include Government Id Check for the bookings.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
Fixed names
2024-11-04 15:28:31 +01:00
- accepted_values:
values:
- W/O Id Check
- With Id Check
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: active_accommodations_per_deal_segmentation
data_type: text
description: |
Segment value based on the number of listings booked in 12 months
for a given deal and date.
tests:
- not_null
- accepted_values:
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
values:
Addressed comments
2024-11-04 14:29:26 +01:00
- "0"
- "01-05"
- "06-20"
- "21-60"
- "61+"
- "UNSET"
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: main_billing_country_iso_3_per_deal
data_type: character varying
description: |
Main billing country of the host aggregated at Deal level.
tests:
- not_null
- name: created_guest_journeys_not_cancelled
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated count of daily guest journeys created, excluding cancelled
Addressed comments
2024-11-04 18:15:13 +01:00
bookings, in a given date and per specified dimension.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
- name: started_guest_journeys_not_cancelled
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated count of daily guest journeys started, excluding cancelled
Addressed comments
2024-11-04 18:15:13 +01:00
bookings, in a given date and per specified dimension.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
- name: completed_guest_journeys_not_cancelled
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated count of daily guest journeys completed, excluding cancelled
Addressed comments
2024-11-04 18:15:13 +01:00
bookings, in a given date and per specified dimension.
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
tests:
- not_null
- name: created_guest_journeys
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated count of daily guest journeys created in a given date and
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
per specified dimension.
tests:
- not_null
- name: started_guest_journeys
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated count of daily guest journeys started in a given date and
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
per specified dimension.
tests:
- not_null
- name: completed_guest_journeys
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated count of daily guest journeys completed in a given date and
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
per specified dimension.
tests:
- not_null
CSAT score
2024-11-04 16:51:24 +01:00
- name: count_csat_score
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated count of guest journeys with CSAT
Addressed comments
2024-11-04 18:15:13 +01:00
(customer satisfaction score) in a given date, dimension, and value..
CSAT score
2024-11-04 16:51:24 +01:00
- name: average_csat_score
data_type: numeric
description: |
final changes
2024-11-05 10:24:17 +01:00
Month-to-date accumulated average CSAT score in a given date, dimension, and value.
CSAT score
2024-11-04 16:51:24 +01:00
tests:
- dbt_expectations.expect_column_values_to_be_between:
min_value: 0
max_value: 5
strictly: false
Fixed names
2024-11-04 15:28:31 +01:00
- name: int_kpis__agg_mtd_check_in_attributed_guest_journeys
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
description: |
This model computes the dimension aggregation for Month-To-Date metrics associated
to Guest Journeys attributed to Check-In date.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: text
description: |
The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
Addressed comments
2024-11-04 14:29:26 +01:00
metric_column_name: created_guest_journeys_not_cancelled
- assert_dimension_completeness:
metric_column_name: started_guest_journeys_not_cancelled
- assert_dimension_completeness:
metric_column_name: completed_guest_journeys_not_cancelled
- assert_dimension_completeness:
metric_column_name: created_guest_journeys
- assert_dimension_completeness:
metric_column_name: started_guest_journeys
- assert_dimension_completeness:
metric_column_name: completed_guest_journeys
CSAT score
2024-11-04 16:51:24 +01:00
- assert_dimension_completeness:
metric_column_name: count_csat_score
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- accepted_values:
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
values:
Addressed comments
2024-11-04 14:29:26 +01:00
- global
- by_deal
- by_has_payment
- by_has_id_check
- by_billing_country
- by_number_of_listings
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
- name: dimension_value
data_type: text
description: |
The value or segment available for the selected dimension.
tests:
- not_null
- name: created_guest_journeys_not_cancelled
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated count of guest journeys created, excluding
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
cancelled bookings, for a given date, dimension, and value.
tests:
- not_null
- name: started_guest_journeys_not_cancelled
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated count of guest journeys started, excluding
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
cancelled bookings, for a given date, dimension, and value.
tests:
- not_null
- name: completed_guest_journeys_not_cancelled
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated count of guest journeys completed, excluding
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
cancelled bookings, for a given date, dimension, and value.
tests:
- not_null
- name: created_guest_journeys
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated count of guest journeys created for a given date,
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
dimension, and value.
tests:
- not_null
- name: started_guest_journeys
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated count of guest journeys started for a given date,
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
dimension, and value.
tests:
- not_null
- name: completed_guest_journeys
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated count of guest journeys completed for a given date,
save all guest journey check in attributed models
2024-11-02 11:28:22 +01:00
dimension, and value.
tests:
Merge branch 'models/23372_csat_guest_kpis' of ssh.dev.azure.com:v3/guardhog/Data/data-dwh-dbt-project into models/23372_csat_guest_kpis Merge issue
2024-11-05 10:36:33 +01:00
- not_null
CSAT score
2024-11-04 16:51:24 +01:00
CSAT score
2024-11-04 16:51:24 +01:00
- name: count_csat_score
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated count of guest journeys with CSAT
(customer satisfaction score) in a given date, dimension, and value.
CSAT score
2024-11-04 16:51:24 +01:00
- name: average_csat_score
data_type: numeric
description: |
Addressed comments
2024-11-04 18:15:13 +01:00
Month-to-date aggregated average CSAT score in a given date,
dimension, and value.
CSAT score
2024-11-04 16:51:24 +01:00
tests:
- dbt_expectations.expect_column_values_to_be_between:
min_value: 0
max_value: 5
strictly: false
Merged PR 3419: Adds Host Resolutions metrics in new KPIs # Description Adds 2 new metrics: - xero_host_resolution_amount_paid_in_gbp - xero_host_resolution_payment_count Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales). We have as usual: - 1 Daily metric model - 2 MTD/Monthly metric model - 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated) - 1 test to compare the values match the current setup # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #23565
2024-11-05 07:45:41 +00:00
- 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.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- id_deal
columns:
- name: date
data_type: date
description: Date of when Host Resolutions transaction happened.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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,
- active_accommodations_per_deal_segmentation.
tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- end_date
- id_deal
- 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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: id_deal
data_type: string
description: Unique identifier of an account.
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.
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.
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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: xero_host_resolution_payment_count
- assert_dimension_completeness:
metric_column_name: xero_host_resolution_amount_paid_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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.
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.
tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
tests:
- assert_dimension_completeness:
metric_column_name: xero_host_resolution_payment_count
- assert_dimension_completeness:
metric_column_name: xero_host_resolution_amount_paid_in_gbp
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
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.
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