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_billable_items description: | This model provides the projected daily billable items, in other words, platform billable bookings and API billable verifications. It considers 2 computations: - The daily billable items for the current month, - The daily billable items in the past 7 days, and the final value is an arithmetic mean of both. This model also retrieves the actual billable items 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: - accepted_values: values: - global - by_number_of_listings - by_billing_country - by_business_scope - by_service - 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_billable_items_for_reporting_source data_type: string description: | The source of the daily billable items for reporting. This field is used to identify the source of the data displayed in daily_billable_items_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_billable_items_for_reporting data_type: integer description: | The daily billable items 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_billable_items_for_evaluation_source data_type: string description: | Important: This field is used to evaluate the performance of the projections! The source of the daily billable items for evaluation. This field is used to identify the source of the data displayed in daily_billable_items_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_billable_items_for_evaluation data_type: integer description: | Important: This field is used to evaluate the performance of the projections! The daily billable items 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_billable_items data_type: integer description: | The projected daily billable items. This field is the result of the projection of the daily billable items for the current month and the past 7 days. data_tests: - not_null - name: actual_daily_billable_items description: | The actual billable items for the same period as the projected ones. This comes from the standard KPIs. data_tests: - not_null - name: same_month_trend_daily_billable_items data_type: float description: | The average daily billable items for the current month. This field is the result of the division of the actual daily billable items 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_billable_items data_type: float description: | The average daily billable items for the past 7 days. This field is the result of the division of the actual daily billable items 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_billable_items data_type: integer description: | The total billable items for the current month. This field is the result of the sum of the actual daily billable items to date. This is just for information purposes. - name: last_7_days_trend_total_billable_items data_type: integer description: | The total billable items for the past 7 days. This field is the result of the sum of the actual daily billable items 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_billable_items description: | This model provides the projected monthly billable items per dimension and dimension value. Billable items are defined as platform billable bookings and API billable verifications. 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: - accepted_values: values: - global - by_number_of_listings - by_billing_country - by_business_scope - by_service - 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_billable_items data_type: integer description: | The projected monthly billable items for the current month. This field is the result of the sum of the actual daily billable items for the current month to date and the projected daily billable items 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_billable_items data_type: integer description: | The sum of the actual daily billable items 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 billable items 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 billable items 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.