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

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Merged PR 4665: Projected Bookings to the end of the current month # Description Computes projected Bookings to the end of the current month per dimension and dimension value KPIs changes: * Adds a int_kpis__agg_daily_created_bookings model. This is a standard KPIs model that computes created bookings at a daily level per dimension and dimension value. Projected KPIs (NEW): * Adds a new folder named projected within KPIs. This includes a simple Readme. * Adds a default dimension dates model that ranges from the past 3 complete months to the end of the current month, that is in the future. * Adds 2 projected models for created bookings: The daily one, that handles the logic of the projection (same month + last 7 days) and the monthly one, that retrieves the end of month projected value as well as some indicators of how good or bad this was for previous months. How good is the projection at 11th of March (so 10 days in the month)? `select * from intermediate.int_kpis_projected__agg_monthly_created_bookings order by actual_created_bookings desc` ![image.png](https://guardhog.visualstudio.com/4148d95f-4b6d-4205-bcff-e9c8e0d2ca65/_apis/git/repositories/54ac356f-aad7-46d2-b62c-e8c5b3bb8ebf/pullRequests/4665/attachments/image.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. - [X] I have checked for DRY opportunities with other models and docs. - [X] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #28251
2025-03-11 14:34:30 +00:00
version: 2
models:
- name: int_kpis_projected__dimension_dates
description: |
This model provides the daily time dimensionality needed
for the projection of KPIs.
It considers:
- Dates from the current month, up to the end of it,
indistinctly if it's in the future or not.
- Dates from the 3 past complete months.
This model is intended to be used as a dimension table for
the projection of KPIs, thus it's expected to be joined with
the fact table containing the KPIs to be projected.
columns:
- name: date
data_type: date
description: Specific date. It's the primary key of this model.
data_tests:
- unique
- not_null
- name: first_day_month
data_type: date
description: |
First day of the month corresponding to the date field.
data_tests:
- not_null
- name: last_day_month
data_type: date
description: |
Last day of the month corresponding to the date field.
data_tests:
- not_null
- name: previous_6_days
data_type: date
description: Date of the previous 6 days with respect to the date field.
data_tests:
- unique
- not_null
- name: is_end_of_month
data_type: boolean
description: True if it's end of month, false otherwise.
data_tests:
- not_null
- name: is_current_month
data_type: boolean
description: |
True if the date is within the current month, false otherwise.
data_tests:
- not_null
- name: is_in_the_future
data_type: boolean
description: |
True if the date is in the future, false otherwise. Note that is in the
future will also include the current day, as we can only consider full-closed
data up to yesterday.
data_tests:
- not_null
- name: is_latest_historical_date
data_type: boolean
description: |
True if the date is the latest historical date, false otherwise.
The latest historical date is the latest date from which we have full information.
This should be yesterday.
data_tests:
- not_null
- name: is_available_for_same_month_projection
data_type: boolean
description: |
True if the date is available for the projection of KPIs for the same month,
false otherwise. This will be true for all days contained within the first day
of the month up to yesterday. This will apply for both the current month and
the 3 months.
If today is 10th of May, and data is available up to 9th of May, then all days
from 1st to 9th of May, April, March and February will be available for projection.
If today is 1st of May, then no dates will be available for projection.
data_tests:
- not_null
- name: is_available_for_last_7_days_projection
data_type: boolean
description: |
True if the date is available for the projection of KPIs for the past 7 days,
false otherwise. This will be true only for yesterday and the equivalent day for
the previous 3 months.
If today is 10th of May, and data is available up to 9th of May, then all days
only 9th of May, 9th of April, 9th of March and 9th of February will be available
for projection.
If today is 1st of May, then 30th of April, 31st of March, 28th of February and
31st of January will be available for projection.
data_tests:
- not_null
- name: int_kpis_projected__agg_daily_created_bookings
description: |
This model provides the projected daily created bookings.
It considers 2 computations:
- The daily created bookings for the current month,
- The daily created bookings in the past 7 days,
and the final value is an arithmetic mean of both.
This model also retrieves the actual created bookings to be able
to compare the projected values with the actual ones.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- date
- dimension
- dimension_value
columns:
- name: date
data_type: date
description: |
The start and end date of the time range considered for the
metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- actual_daily_created_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: first_day_month
data_type: date
description: |
First day of the month corresponding to the date field.
data_tests:
- not_null
- name: last_day_month
data_type: date
description: |
Last day of the month corresponding to the date field.
data_tests:
- not_null
- name: is_end_of_month
data_type: boolean
description: True if it's end of month, false otherwise.
data_tests:
- not_null
- name: is_current_month
data_type: boolean
description: |
True if the date is within the current month, false otherwise.
data_tests:
- not_null
- name: is_in_the_future
data_type: boolean
description: |
True if the date is in the future, false otherwise. Note that is in the
future will also include the current day, as we can only consider full-closed
data up to yesterday.
data_tests:
- not_null
- name: is_latest_historical_date
data_type: boolean
description: |
True if the date is the latest historical date, false otherwise.
The latest historical date is the latest date from which we have full information.
This should be yesterday.
data_tests:
- not_null
- name: daily_created_bookings_for_reporting_source
data_type: string
description: |
The source of the daily created bookings for reporting.
This field is used to identify the source of the data displayed
in daily_created_bookings_for_reporting to differentiate between
the actual and projected values.
It's aimed for reforting purposes as any historical month will
contain the actual figures.
data_tests:
- not_null
- accepted_values:
values:
- ACTUAL
- PROJECTED
- name: daily_created_bookings_for_reporting
data_type: integer
description: |
The daily created bookings for reporting purposes.
This field contains both the actual and projected values.
Any date in the future will contain projected values, while
any date in the past will contain actual values.
data_tests:
- not_null
- name: daily_created_bookings_for_evaluation_source
data_type: string
description: |
Important: This field is used to evaluate the performance
of the projections!
The source of the daily created bookings for evaluation.
This field is used to identify the source of the data displayed
in daily_created_bookings_for_evaluation to differentiate between
the actual and projected values.
It's aimed for evaluation purposes as any historical month can
contain projected figures.
data_tests:
- not_null
- accepted_values:
values:
- ACTUAL
- PROJECTED
- name: daily_created_bookings_for_evaluation
data_type: integer
description: |
Important: This field is used to evaluate the performance
of the projections!
The daily created bookings for evaluation purposes.
This field contains both the actual and projected values.
Any date in the future will contain projected values. Any date
in the past which day is after the yesterday day will also contain
projected values. Any date in the past which day is before the
yesterday day will contain actual values.
data_tests:
- not_null
- name: projected_daily_created_bookings
data_type: integer
description: |
The projected daily created bookings. This field is the result
of the projection of the daily created bookings for the current month
and the past 7 days.
data_tests:
- not_null
- name: actual_daily_created_bookings
description: |
The actual created bookings for the same period as the projected ones.
This comes from the standard KPIs.
data_tests:
- not_null
- name: same_month_trend_daily_created_bookings
data_type: float
description: |
The average daily created bookings for the current month.
This field is the result of the division of the actual daily created
bookings to date by the number of days available within the current month
to date, and contains decimals.
This is just for information purposes.
data_tests:
- not_null
- name: last_7_days_trend_daily_created_bookings
data_type: float
description: |
The average daily created bookings for the past 7 days.
This field is the result of the division of the actual daily created
bookings for the past 7 days by 7 days, and contains decimals.
This is just for information purposes.
data_tests:
- not_null
- name: same_month_trend_total_created_bookings
data_type: integer
description: |
The total created bookings for the current month.
This field is the result of the sum of the actual daily created
bookings to date.
This is just for information purposes.
- name: last_7_days_trend_total_created_bookings
data_type: integer
description: |
The total created bookings for the past 7 days.
This field is the result of the sum of the actual daily created
bookings for the past 7 days.
This is just for information purposes.
- name: same_month_trend_total_available_days
data_type: integer
description: |
The total available days for the current month.
This field is the result of the count of the days available within
the current month to date.
This is just for information purposes.
- name: last_7_days_trend_total_available_days
data_type: integer
description: |
The total available days for the past 7 days.
This field is the result of the count of the days available for the
past 7 days.
This is just for information purposes.
- name: int_kpis_projected__agg_monthly_created_bookings
description: |
This model provides the projected monthly created bookings per dimension
and dimension value. It only considers the current month.
Historical data is considered only to assess the performance of the
projections.
The projection logic is handled on the equivalent daily model,
please refer to it for more information.
data_tests:
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- dimension
- dimension_value
columns:
- name: start_date
data_type: date
description: |
The start date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: end_date
data_type: date
description: |
The end date of the time range considered for the metrics in this record.
data_tests:
- not_null
- name: dimension
data_type: string
description: The dimension or granularity of the metrics.
data_tests:
- assert_dimension_completeness:
metric_column_names:
- actual_created_bookings
- accepted_values:
values:
- global
- by_number_of_listings
- by_billing_country
- by_business_scope
- by_deal
- name: dimension_value
data_type: string
description: The value or segment available for the selected dimension.
data_tests:
- not_null
- name: current_month_projected_created_bookings
data_type: integer
description: |
The projected monthly created bookings for the current month.
This field is the result of the sum of the actual daily created bookings
for the current month to date and the projected daily created bookings
for the rest of the days in the month that are in the future.
The closest we are to the end of the month, the more accurate this value will be.
In order to check how good or bad the projection is, please refer to the
historical_monthly_mean_absolute_error and
historical_monthly_mean_absolute_percentage_error fields.
data_tests:
- not_null
- name: actual_created_bookings
data_type: integer
description: |
The sum of the actual daily created bookings for the current month to date.
This comes from the standard KPIs.
data_tests:
- not_null
- name: historical_monthly_mean_absolute_error
data_type: float
description: |
The mean absolute error for this dimension and dimension value.
This field is used to assess the performance of the projections.
This is based on the absolute differences between the projected
monthly created bookings for each previous month vs the actual value.
In order to be consistent, it uses the same number of days available
for the current month to date as the actual value, and the rest of the days
are projected.
This computation is applied for the past 3 months, and the value displayed
here is an average of the absolute differences.
The closest to 0, the better the projection.
- name: historical_monthly_mean_absolute_percentage_error
data_type: float
description: |
The mean absolute percentage error for this dimension and dimension value.
This field is used to assess the performance of the projections.
This is based on the absolute percentage differences between the projected
monthly created bookings for each previous month vs the actual value.
In order to be consistent, it uses the same number of days available
for the current month to date as the actual value, and the rest of the days
are projected.
This computation is applied for the past 3 months, and the value displayed
here is an average of the absolute percentage differences.
The closest to 0, the better the projection.
Reference in a new issue Copy permalink