data-dwh-dbt-project/macros/business_kpis_configuration.sql

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/*
Macro: get_kpi_dimensions_for_production
Provides the list of Dimensions that will be available in production for the Main KPIs.
It provides a proper display name for reporting purposes.
*/
{% macro get_kpi_dimensions_for_production() %}
{% set dimensions = [
{"dimension": "'global'", "dimension_display": "'Global'"},
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...
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{
"dimension": "'by_number_of_listings'",
"dimension_display": "'By # of Listings Booked in 12 Months'",
},
{
"dimension": "'by_billing_country'",
"dimension_display": "'By Billing Country'",
},
] %}
{{ return(dimensions) }}
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
{% endmacro %}
/*
The following lines specify for each dimension the field to be used in a
standalone macro.
Please note that strings should be encoded with " ' your_value_here ' ",
while fields from tables should be specified like " your_field_here "
*/
{% macro dim_global() %}
{{ return({"dimension": "'global'", "dimension_value": "'global'"}) }}
{% endmacro %}
{% macro dim_billing_country() %}
{{
return(
{
"dimension": "'by_billing_country'",
"dimension_value": "main_billing_country_iso_3_per_deal",
}
)
}}
{% endmacro %}
{% macro dim_number_of_listings() %}
{{
return(
{
"dimension": "'by_number_of_listings'",
"dimension_value": "active_accommodations_per_deal_segmentation",
}
)
}}
{% endmacro %}
{% macro dim_deal() %}
{{ return({"dimension": "'by_deal'", "dimension_value": "id_deal"}) }}
{% endmacro %}
{% macro dim_dash() %}
{{ return({"dimension": "'by_dash_source'", "dimension_value": "dash_source"}) }}
{% endmacro %}
{% macro dim_has_payment() %}
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{{ return({"dimension": "'by_has_payment'", "dimension_value": "has_payment"}) }}
{% endmacro %}
{% macro dim_has_id_check() %}
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{{ return({"dimension": "'by_has_id_check'", "dimension_value": "has_id_check"}) }}
{% endmacro %}
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
/*
Macro: get_kpi_dimensions_per_model
Provides a general assignement for the Dimensions available for each KPI
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
model. Keep in mind that these assignations need to be previously
declared.
*/
{% macro get_kpi_dimensions_per_model(entity_name) %}
{# Base dimensions shared by all models #}
{% set base_dimensions = [
dim_global(),
dim_number_of_listings(),
dim_billing_country(),
] %}
{# Initialize a list to hold any model-specific dimensions #}
{% set additional_dimensions = [] %}
{# Adds Deal dimension to all models except DEAL metrics #}
{% if entity_name != "DEALS" %}
{% set additional_dimensions = additional_dimensions + [dim_deal()] %}
{% endif %}
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
{# Add entity-specific dimensions #}
{% if entity_name == "CREATED_BOOKINGS" %}
{% set additional_dimensions = additional_dimensions + [dim_dash()] %}
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
{% endif %}
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{% if entity_name == "CHECK_IN_ATTRIBUTED_GUEST_JOURNEYS" %}
{% set additional_dimensions = additional_dimensions + [
dim_has_payment(),
dim_has_id_check(),
] %}
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{% endif %}
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{% if entity_name == "GUEST_PAYMENTS" %}
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{% set additional_dimensions = additional_dimensions + [
dim_has_id_check(),
] %}
{% endif %}
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
{# Combine base dimensions with additional dimensions for the specific model #}
{% set dimensions = base_dimensions + additional_dimensions %}
{{ return(dimensions) }}
{% endmacro %}