Merged PR 3137: Growth score to reporting

# Description

Copies intermediate to reporting for growth score by deal. Schema is copy-paste from intermediate changing the model's name.

# 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: #22635

models/intermediate/cross/int_monthly_growth_score_by_deal.sql

@@ -74,6 +74,7 @@ with
             -- Dates - For Information Purposes
             given_month.first_day_month as given_month_first_day_month,
             previous_1_month.first_day_month as previous_1_month_first_day_month,
+            previous_2_month.first_day_month as previous_2_month_first_day_month,
             previous_12_month.first_day_month as previous_12_month_first_day_month,
             previous_13_month.first_day_month as previous_13_month_first_day_month,
             aggregated_revenue.from_first_day_month
@@ -84,6 +85,7 @@ with
             -- Revenue --
             given_month.revenue_in_gbp as given_month_revenue_in_gbp,
             previous_1_month.revenue_in_gbp as previous_1_month_revenue_in_gbp,
+            previous_2_month.revenue_in_gbp as previous_2_month_revenue_in_gbp,
             previous_12_month.revenue_in_gbp as previous_12_month_revenue_in_gbp,
             previous_13_month.revenue_in_gbp as previous_13_month_revenue_in_gbp,
             -- In these YoY and MoM computations, if negative revenue is found,
@@ -92,6 +94,9 @@ with
             nullif(greatest(given_month.revenue_in_gbp, 0), 0)
             / nullif(greatest(previous_1_month.revenue_in_gbp, 0), 0)
             - 1 as mom_revenue_growth,
+            nullif(greatest(previous_1_month.revenue_in_gbp, 0), 0)
+            / nullif(greatest(previous_2_month.revenue_in_gbp, 0), 0)
+            - 1 as mom_1_month_shift_revenue_growth,
             nullif(greatest(given_month.revenue_in_gbp, 0), 0)
             / nullif(greatest(previous_12_month.revenue_in_gbp, 0), 0)
             - 1 as yoy_revenue_growth,
@@ -146,6 +151,12 @@ with
             on previous_1_month.first_day_month + interval '1 months'
             = given_month.first_day_month
             and previous_1_month.id_deal = given_month.id_deal
+        -- Retrieve monthly data from same deal and 2 months ago
+        left join
+            deal_history_from_previous_months as previous_2_month
+            on previous_2_month.first_day_month + interval '2 months'
+            = given_month.first_day_month
+            and previous_2_month.id_deal = given_month.id_deal
         -- Retrieve monthly data from same deal and the equivalent
         -- month from last year
         left join
@@ -154,8 +165,7 @@ with
             = given_month.first_day_month
             and previous_12_month.id_deal = given_month.id_deal
         -- Retrieve monthly data from same deal and the equivalent
-        -- month from last
+        -- month from last year and 1 month before
-        -- year and 1 month before
         left join
             deal_history_from_previous_months as previous_13_month
             on previous_13_month.first_day_month + interval '13 months'
@@ -166,62 +176,124 @@ with
             revenue_12_months_window_aggregation_per_deal aggregated_revenue
             on aggregated_revenue.id_deal = given_month.id_deal
             and aggregated_revenue.first_day_month = given_month.first_day_month
+    ),
+    growth_score_computation as (
+        select
+            m.date,
+            m.id_deal,
+
+            m.main_deal_name,
+            m.main_billing_country_iso_3_per_deal,
+            m.deal_lifecycle_state,
+
+            m.given_month_first_day_month,
+            m.previous_1_month_first_day_month,
+            m.previous_2_month_first_day_month,
+            m.previous_12_month_first_day_month,
+            m.previous_13_month_first_day_month,
+            m.aggregated_revenue_from_first_day_month,
+            m.aggregated_revenue_to_first_day_month,
+
+            m.given_month_revenue_in_gbp,
+            m.previous_1_month_revenue_in_gbp,
+            m.previous_2_month_revenue_in_gbp,
+            m.previous_12_month_revenue_in_gbp,
+            m.previous_13_month_revenue_in_gbp,
+            cast(m.mom_revenue_growth as numeric(19, 6)) as mom_revenue_growth,
+            cast(
+                m.mom_1_month_shift_revenue_growth as numeric(19, 6)
+            ) as mom_1_month_shift_revenue_growth,
+            cast(m.yoy_revenue_growth as numeric(19, 6)) as yoy_revenue_growth,
+            cast(
+                m.yoy_1_month_shift_revenue_growth as numeric(19, 6)
+            ) as yoy_1_month_shift_revenue_growth,
+
+            m.given_month_created_bookings,
+            m.previous_1_month_created_bookings,
+            m.previous_12_month_created_bookings,
+            cast(
+                m.mom_created_bookings_growth as numeric(19, 6)
+            ) as mom_created_bookings_growth,
+            cast(
+                m.yoy_created_bookings_growth as numeric(19, 6)
+            ) as yoy_created_bookings_growth,
+
+            m.given_month_listings_booked_in_month,
+            m.previous_1_month_listings_booked_in_month,
+            m.previous_12_month_listings_booked_in_month,
+            cast(
+                m.mom_listings_booked_in_month_growth as numeric(19, 6)
+            ) as mom_listings_booked_in_month_growth,
+            cast(
+                m.yoy_listings_booked_in_month_growth as numeric(19, 6)
+            ) as yoy_listings_booked_in_month_growth,
+
+            m.deal_revenue_12_months_window,
+            m.effective_deal_revenue_12_months_window,
+            m.effective_global_revenue_12_months_window,
+            m.deal_contribution_share_to_global_revenue,
+            m.deal_contribution_rank_to_global_revenue,
+
+            cast(
+                (
+                    coalesce(m.mom_created_bookings_growth, 0)
+                    + coalesce(m.mom_listings_booked_in_month_growth, 0)
+                    + coalesce(m.mom_1_month_shift_revenue_growth, 0)
+                )
+                / 3 as numeric(19, 6)
+            ) as avg_mom_growth_score,
+
+            cast(
+                (
+                    coalesce(m.yoy_created_bookings_growth, 0)
+                    + coalesce(m.yoy_listings_booked_in_month_growth, 0)
+                    + coalesce(m.yoy_1_month_shift_revenue_growth, 0)
+                )
+                / 3 as numeric(19, 6)
+            ) as avg_yoy_growth_score,
+            cast(
+                (
+                    coalesce(m.yoy_created_bookings_growth, 0)
+                    + coalesce(m.yoy_listings_booked_in_month_growth, 0)
+                    + coalesce(m.yoy_1_month_shift_revenue_growth, 0)
+                    + coalesce(m.mom_created_bookings_growth, 0)
+                    + coalesce(m.mom_listings_booked_in_month_growth, 0)
+                    + coalesce(m.mom_1_month_shift_revenue_growth, 0)
+                )
+                / 6 as numeric(19, 6)
+            ) as avg_growth_score,
+            cast(
+                (
+                    (
+                        coalesce(m.yoy_created_bookings_growth, 0)
+                        + coalesce(m.yoy_listings_booked_in_month_growth, 0)
+                        + coalesce(m.yoy_1_month_shift_revenue_growth, 0)
+                        + coalesce(m.mom_created_bookings_growth, 0)
+                        + coalesce(m.mom_listings_booked_in_month_growth, 0)
+                        + coalesce(m.mom_1_month_shift_revenue_growth, 0)
+                    )
+                    / 6
+                )
+                * deal_contribution_share_to_global_revenue as numeric(19, 6)
+            ) as weighted_avg_growth_score
+
+        from metrics_attribution_to_given_month_per_deal m
     )
 select
-    m.date,
+    *,
-    m.id_deal,
+    -- Applies a categorisation based on the score value. These scores thresholds are
-
+    -- opinionated
-    m.main_deal_name,
+    case
-    m.main_billing_country_iso_3_per_deal,
+        when weighted_avg_growth_score <= -0.001
-    m.deal_lifecycle_state,
+        then 'TOP LOSER'
-
+        when weighted_avg_growth_score > -0.001 and weighted_avg_growth_score < 0
-    m.given_month_first_day_month,
+        then 'LOSER'
-    m.previous_1_month_first_day_month,
+        when weighted_avg_growth_score = 0
-    m.previous_12_month_first_day_month,
+        then 'FLAT'
-    m.previous_13_month_first_day_month,
+        when weighted_avg_growth_score > 0 and weighted_avg_growth_score < 0.001
-    m.aggregated_revenue_from_first_day_month,
+        then 'WINNER'
-    m.aggregated_revenue_to_first_day_month,
+        when weighted_avg_growth_score >= 0.001
-
+        then 'TOP WINNER'
-    m.given_month_revenue_in_gbp,
+        else 'UNSET'
-    m.previous_1_month_revenue_in_gbp,
+    end as categorisation_weighted_avg_growth_score
-    m.previous_12_month_revenue_in_gbp,
+from growth_score_computation
-    m.previous_13_month_revenue_in_gbp,
-    m.mom_revenue_growth,
-    m.yoy_revenue_growth,
-    m.yoy_1_month_shift_revenue_growth,
-
-    m.given_month_created_bookings,
-    m.previous_1_month_created_bookings,
-    m.previous_12_month_created_bookings,
-    m.mom_created_bookings_growth,
-    m.yoy_created_bookings_growth,
-
-    m.given_month_listings_booked_in_month,
-    m.previous_1_month_listings_booked_in_month,
-    m.previous_12_month_listings_booked_in_month,
-    m.mom_listings_booked_in_month_growth,
-    m.yoy_listings_booked_in_month_growth,
-
-    m.deal_revenue_12_months_window,
-    m.effective_deal_revenue_12_months_window,
-    m.effective_global_revenue_12_months_window,
-    m.deal_contribution_share_to_global_revenue,
-    m.deal_contribution_rank_to_global_revenue,
-
-    (
-        coalesce(m.yoy_created_bookings_growth, 0)
-        + coalesce(m.yoy_listings_booked_in_month_growth, 0)
-        + coalesce(m.yoy_1_month_shift_revenue_growth, 0)
-    )
-    / 3 as avg_growth_score,
-    (
-        (
-            coalesce(m.yoy_created_bookings_growth, 0)
-            + coalesce(m.yoy_listings_booked_in_month_growth, 0)
-            + coalesce(m.yoy_1_month_shift_revenue_growth, 0)
-        )
-        / 3
-    )
-    * deal_contribution_share_to_global_revenue as weighted_avg_growth_score
-
-from metrics_attribution_to_given_month_per_deal m

models/intermediate/cross/schema.yml

@@ -605,11 +605,12 @@ models:
       - Total revenue (in gbp)
 
       The main idea is, for each deal, to compare each of these metrics by 
-      checking the latest monthly value vs. the monthly value of the equivalent 
+      checking the latest monthly value vs. 1) the monthly value of the equivalent 
-      month on the previous year - in other words, a year-on-year (YoY) comparison.
+      month on the previous year and 2) the monthly value of the previous month
+      - in other words, a year-on-year (YoY) and month-on-month (MoM) comparison.
       We do this comparison by doing a relative incremental.
 
-      The growth score is computed then by averaging the outcome of the 3 scores. 
+      The growth score is computed then by averaging the outcome of the 6 scores. 
       Lastly, in order to provide a prioritisation sense, we have a weighted growth 
       score that results from the multiplication of the growth score per the revenue 
       weight a specific deal has provided in the previous 12 months.
@@ -687,6 +688,15 @@ models:
           It can be null if no previous history for that 
           deal is found.
 
+      - name: previous_2_month_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          month 2 months before with respect to date. 
+          If date = 2024-09-30, this field will be 2024-07-01.
+          It can be null if no previous history for that 
+          deal is found.
+
       - name: previous_12_month_first_day_month
         data_type: date
         description: |
@@ -749,12 +759,22 @@ models:
           This value can be null, thus indicating that no 
           history is available.
 
+      - name: previous_2_month_revenue_in_gbp
+        data_type: decimal
+        description: |
+          Monthly value representing revenue in GBP 
+          for a specific deal. This value corresponds to 
+          the monthly amount generated 2 months ago
+          This value can be negative. 
+          This value can be null, thus indicating that no 
+          history is available.
+
       - name: previous_12_month_revenue_in_gbp
         data_type: decimal
         description: |
           Monthly value representing revenue in GBP 
           for a specific deal. This value corresponds to 
-          monthly amount generated 12 months ago. 
+          the monthly amount generated 12 months ago. 
           This value can be negative. 
           This value can be null, thus indicating that no 
           history is available.
@@ -764,7 +784,7 @@ models:
         description: |
           Monthly value representing revenue in GBP 
           for a specific deal. This value corresponds to 
-          monthly amount generated 13 months ago. 
+          the monthly amount generated 13 months ago. 
           This value can be negative. 
           This value can be null, thus indicating that no 
           history is available.
@@ -782,6 +802,20 @@ models:
               min_value: -1
               strictly: false
 
+      - name: mom_1_month_shift_revenue_growth
+        data_type: decimal
+        description: |
+          Relative increment of the revenue generated in the 
+          previous month with respect to the one generated 2
+          months ago. 
+          It can be null if any revenue used in the computation
+          is null or it's negative.
+          This field is used for the growth score computation.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
       - name: yoy_revenue_growth
         data_type: decimal
         description: |
@@ -855,6 +889,7 @@ models:
           the previous month. 
           It can be null if the bookings created in the 
           previous month are null.
+          This field is used for the growth score computation.
         tests:
           - dbt_expectations.expect_column_values_to_be_between:
               min_value: -1
@@ -920,6 +955,7 @@ models:
           the previous month. 
           It can be null if the listings booked in month in the 
           previous month are null.
+          This field is used for the growth score computation.
         tests:
           - dbt_expectations.expect_column_values_to_be_between:
               min_value: -1
@@ -1007,7 +1043,18 @@ models:
         tests:
           - not_null
 
-      - name: avg_growth_score
+      - name: avg_mom_growth_score
+        data_type: decimal
+        description: |
+          Represents the average score of MoM growth of created 
+          bookings, MoM growth of listings booked in month and 
+          MoM shifted by one month of revenue.
+          It indicates the tendency of growth of the deal without 
+          taking into account its revenue size. It cannot be null.
+        tests:
+          - not_null
+
+      - name: avg_yoy_growth_score
         data_type: decimal
         description: |
           Represents the average score of YoY growth of created 
@@ -1018,6 +1065,17 @@ models:
         tests:
           - not_null
 
+      - name: avg_growth_score
+        data_type: decimal
+        description: |
+          Represents the average score of YoY and MoM growth of created 
+          bookings, YoY and MoM growth of listings booked in month and 
+          YoY and MoM shifted by one month of revenue.
+          It indicates the tendency of growth of the deal without 
+          taking into account its revenue size. It cannot be null.
+        tests:
+          - not_null
+
       - name: weighted_avg_growth_score
         data_type: decimal
         description: |
@@ -1029,3 +1087,22 @@ models:
           the financial impact this deal tendency can have.
         tests:
           - not_null
+
+      - name: categorisation_weighted_avg_growth_score
+        data_type: string
+        description: |
+          Discrete categorisation of weighted_avg_growth_score.
+          It helps easily identifying which accounts are top losers, 
+          losers, flat, winners and top winners. 
+          Currently the categorisation is based on the score itself 
+          rather than selecting a top up/down.
+        tests:
+          - not_null
+          - accepted_values:
+              values:
+                - TOP LOSER
+                - LOSER
+                - FLAT
+                - WINNER
+                - TOP WINNER
+                - UNSET

models/reporting/general/monthly_growth_score_by_deal.sql

@@ -0,0 +1,61 @@
+with
+    int_monthly_growth_score_by_deal as (
+        select * from {{ ref("int_monthly_growth_score_by_deal") }}
+    )
+select
+    date as date,
+    id_deal as id_deal,
+
+    main_deal_name as main_deal_name,
+    main_billing_country_iso_3_per_deal as main_billing_country_iso_3_per_deal,
+    deal_lifecycle_state as deal_lifecycle_state,
+
+    given_month_first_day_month as given_month_first_day_month,
+    previous_1_month_first_day_month as previous_1_month_first_day_month,
+    previous_2_month_first_day_month as previous_2_month_first_day_month,
+    previous_12_month_first_day_month as previous_12_month_first_day_month,
+    previous_13_month_first_day_month as previous_13_month_first_day_month,
+    aggregated_revenue_from_first_day_month as aggregated_revenue_from_first_day_month,
+    aggregated_revenue_to_first_day_month as aggregated_revenue_to_first_day_month,
+
+    given_month_revenue_in_gbp as given_month_revenue_in_gbp,
+    previous_1_month_revenue_in_gbp as previous_1_month_revenue_in_gbp,
+    previous_2_month_revenue_in_gbp as previous_2_month_revenue_in_gbp,
+    previous_12_month_revenue_in_gbp as previous_12_month_revenue_in_gbp,
+    previous_13_month_revenue_in_gbp as previous_13_month_revenue_in_gbp,
+    mom_revenue_growth as mom_revenue_growth,
+    mom_1_month_shift_revenue_growth as mom_1_month_shift_revenue_growth,
+    yoy_revenue_growth as yoy_revenue_growth,
+    yoy_1_month_shift_revenue_growth as yoy_1_month_shift_revenue_growth,
+
+    given_month_created_bookings as given_month_created_bookings,
+    previous_1_month_created_bookings as previous_1_month_created_bookings,
+    previous_12_month_created_bookings as previous_12_month_created_bookings,
+    mom_created_bookings_growth as mom_created_bookings_growth,
+    yoy_created_bookings_growth as yoy_created_bookings_growth,
+
+    given_month_listings_booked_in_month as given_month_listings_booked_in_month,
+    previous_1_month_listings_booked_in_month
+    as previous_1_month_listings_booked_in_month,
+    previous_12_month_listings_booked_in_month
+    as previous_12_month_listings_booked_in_month,
+    mom_listings_booked_in_month_growth as mom_listings_booked_in_month_growth,
+    yoy_listings_booked_in_month_growth as yoy_listings_booked_in_month_growth,
+
+    deal_revenue_12_months_window as deal_revenue_12_months_window,
+    effective_deal_revenue_12_months_window as effective_deal_revenue_12_months_window,
+    effective_global_revenue_12_months_window
+    as effective_global_revenue_12_months_window,
+    deal_contribution_share_to_global_revenue
+    as deal_contribution_share_to_global_revenue,
+    deal_contribution_rank_to_global_revenue
+    as deal_contribution_rank_to_global_revenue,
+
+    avg_mom_growth_score as avg_mom_growth_score,
+    avg_yoy_growth_score as avg_yoy_growth_score,
+    avg_growth_score as avg_growth_score,
+    weighted_avg_growth_score as weighted_avg_growth_score,
+
+    categorisation_weighted_avg_growth_score as categorisation_weighted_avg_growth_score
+
+from int_monthly_growth_score_by_deal

models/reporting/general/schema.yml

@@ -514,3 +514,520 @@ models:
         description: day monthly number of the given date.
         tests:
           - not_null
+
+  - name: monthly_growth_score_by_deal
+    description: |
+      The main goal of this model is to provide a growth score by deal and month. 
+      The idea behind it is that each deal will have some business performance 
+      associated to it over the months, and that comparing how it is currently
+      performing vs. historical data we can determine whether the tendency is to 
+      grow or to decay. This is specially useful for AMs to focus their effort 
+      towards the clients that have a negative tendency.
+
+      The computation of the growth score is based on 3 main indicators:
+      - Created bookings 
+      - Listings booked in month 
+      - Total revenue (in gbp)
+
+      The main idea is, for each deal, to compare each of these metrics by 
+      checking the latest monthly value vs. 1) the monthly value of the equivalent 
+      month on the previous year and 2) the monthly value of the previous month
+      - in other words, a year-on-year (YoY) and month-on-month (MoM) comparison.
+      We do this comparison by doing a relative incremental.
+
+      The growth score is computed then by averaging the outcome of the 6 scores. 
+      Lastly, in order to provide a prioritisation sense, we have a weighted growth 
+      score that results from the multiplication of the growth score per the revenue 
+      weight a specific deal has provided in the previous 12 months.
+
+      However, this is not strictly true for Revenue because 1) we have an invoicing 
+      delay and 2) in some cases, monthly revenue per deal can be negative. In this 
+      specific cases, the YoY comparison is shifted by one month, and an effective 
+      revenue value for the revenue share is computed, that cannot be lower than 0. 
+
+      In order to keep both a properly set up score and revenue consistency, both 
+      a real revenue value and effective revenue value are present in this model, 
+      while no MoM or YoY value is computed if negative revenue is found.  
+
+      Lastly, this model provides informative date fields, deal attributes, absolute
+      metric values and MoM & YoY relative incrementals to enrich reporting.
+
+    tests:
+      - dbt_utils.unique_combination_of_columns:
+          combination_of_columns:
+            - date
+            - id_deal
+
+    columns:
+      - name: date
+        data_type: date
+        description: |
+          Date corresponding to the last day of the month. Given month 
+          metrics are inclusive to this date. Together with id_deal, it 
+          acts as the primary key of this model.
+        tests:
+          - not_null
+
+      - name: id_deal
+        data_type: string
+        description: |
+          Unique identifier of a Deal. Together with date, it acts as 
+          the primary key of this model.
+        tests:
+          - not_null
+
+      - name: main_deal_name
+        data_type: string
+        description: |
+          Main name for a Deal, representing the client.
+        tests:
+          - not_null
+
+      - name: main_billing_country_iso_3_per_deal
+        data_type: string
+        description: |
+          Main billing country for this client. In some cases 
+          it can be null.
+
+      - name: deal_lifecycle_state
+        data_type: string
+        description: |
+          Identifier of the lifecycle state of a given deal 
+          in a given month.
+
+      - name: given_month_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          month corresponding to date. 
+          If date = 2024-09-30, this field will be 2024-09-01.
+        tests:
+          - not_null
+
+      - name: previous_1_month_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          previous month with respect to date. 
+          If date = 2024-09-30, this field will be 2024-08-01.
+          It can be null if no previous history for that 
+          deal is found.
+
+      - name: previous_2_month_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          month 2 months before with respect to date. 
+          If date = 2024-09-30, this field will be 2024-07-01.
+          It can be null if no previous history for that 
+          deal is found.
+
+      - name: previous_12_month_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          month with respect to date, but on the previous year. 
+          If date = 2024-09-30, this field will be 2023-09-01.
+          It can be null if no previous history for that 
+          deal is found.
+
+      - name: previous_13_month_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          previous month with respect to date, but on the previous year. 
+          If date = 2024-09-30, this field will be 2023-08-01.
+          It can be null if no previous history for that 
+          deal is found.
+
+      - name: aggregated_revenue_from_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          month from the lower bound range in which the revenue 
+          aggregation is computed.
+          The aggregation uses the previous 12 months in which we 
+          know the revenue, thus:
+          If date = 2024-09-30, this field will be 2023-09-01.
+          It can be null if no previous history for that 
+          deal is found.
+
+      - name: aggregated_revenue_to_first_day_month
+        data_type: date
+        description: |
+          Informative field. It indicates the first day of the 
+          month from the upper bound range in which the revenue 
+          aggregation is computed.
+          The aggregation uses the previous 12 months in which we 
+          know the revenue, thus:
+          If date = 2024-09-30, this field will be 2023-08-01.
+          It can be null if no previous history for that 
+          deal is found.
+
+      - name: given_month_revenue_in_gbp
+        data_type: decimal
+        description: |
+          Monthly value representing revenue in GBP 
+          for a specific deal. This value corresponds to 
+          the given month. This value can be negative,
+          but not null.
+        tests:
+          - not_null
+
+      - name: previous_1_month_revenue_in_gbp
+        data_type: decimal
+        description: |
+          Monthly value representing revenue in GBP 
+          for a specific deal. This value corresponds to 
+          the previous month. 
+          This value can be negative. 
+          This value can be null, thus indicating that no 
+          history is available.
+
+      - name: previous_2_month_revenue_in_gbp
+        data_type: decimal
+        description: |
+          Monthly value representing revenue in GBP 
+          for a specific deal. This value corresponds to 
+          the monthly amount generated 2 months ago
+          This value can be negative. 
+          This value can be null, thus indicating that no 
+          history is available.
+
+      - name: previous_12_month_revenue_in_gbp
+        data_type: decimal
+        description: |
+          Monthly value representing revenue in GBP 
+          for a specific deal. This value corresponds to 
+          the monthly amount generated 12 months ago. 
+          This value can be negative. 
+          This value can be null, thus indicating that no 
+          history is available.
+
+      - name: previous_13_month_revenue_in_gbp
+        data_type: decimal
+        description: |
+          Monthly value representing revenue in GBP 
+          for a specific deal. This value corresponds to 
+          the monthly amount generated 13 months ago. 
+          This value can be negative. 
+          This value can be null, thus indicating that no 
+          history is available.
+
+      - name: mom_revenue_growth
+        data_type: decimal
+        description: |
+          Relative increment of the revenue generated in the 
+          current month with respect to the one generated in 
+          the previous month. 
+          It can be null if any revenue used in the computation
+          is null or it's negative.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: mom_1_month_shift_revenue_growth
+        data_type: decimal
+        description: |
+          Relative increment of the revenue generated in the 
+          previous month with respect to the one generated 2
+          months ago. 
+          It can be null if any revenue used in the computation
+          is null or it's negative.
+          This field is used for the growth score computation.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: yoy_revenue_growth
+        data_type: decimal
+        description: |
+          Relative increment of the revenue generated in the 
+          current month with respect to the one generated 12
+          months ago. 
+          It can be null if any revenue used in the computation
+          is null or it's negative.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: yoy_1_month_shift_revenue_growth
+        data_type: decimal
+        description: |
+          Relative increment of the revenue generated in the 
+          previous month with respect to the one generated 13
+          months ago. 
+          It can be null if any revenue used in the computation
+          is null or it's negative.
+          This field is used for the growth score computation.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: given_month_created_bookings
+        data_type: integer
+        description: |
+          Monthly value representing created bookings
+          for a specific deal. This value corresponds to 
+          the given month. This value cannot be null.
+        tests:
+          - not_null
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: previous_1_month_created_bookings
+        data_type: integer
+        description: |
+          Monthly value representing created bookings
+          for a specific deal. This value corresponds to 
+          the previous month. 
+          This value can be null, thus indicating that no 
+          history is available.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: previous_12_month_created_bookings
+        data_type: integer
+        description: |
+          Monthly value representing created bookings 
+          for a specific deal. This value corresponds to 
+          monthly amount generated 12 months ago. 
+          This value can be null, thus indicating that no 
+          history is available.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: mom_created_bookings_growth
+        data_type: decimal
+        description: |
+          Relative increment of the bookings created in the 
+          current month with respect to the ones created in 
+          the previous month. 
+          It can be null if the bookings created in the 
+          previous month are null.
+          This field is used for the growth score computation.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: yoy_created_bookings_growth
+        data_type: decimal
+        description: |
+          Relative increment of the bookings created in the 
+          current month with respect to the ones created 12
+          months ago. 
+          It can be null if the bookings created 12 months 
+          ago are null. 
+          This field is used for the growth score computation.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: given_month_listings_booked_in_month
+        data_type: integer
+        description: |
+          Monthly value representing the listings booked in month
+          for a specific deal. This value corresponds to 
+          the given month. This value cannot be null.
+        tests:
+          - not_null
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: previous_1_month_listings_booked_in_month
+        data_type: integer
+        description: |
+          Monthly value representing the listings booked in month
+          for a specific deal. This value corresponds to 
+          the previous month. 
+          This value can be null, thus indicating that no 
+          history is available.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: previous_12_month_listings_booked_in_month
+        data_type: integer
+        description: |
+          Monthly value representing the listings booked in month
+          for a specific deal. This value corresponds to 
+          monthly amount generated 12 months ago. 
+          This value can be null, thus indicating that no 
+          history is available.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: mom_listings_booked_in_month_growth
+        data_type: decimal
+        description: |
+          Relative increment of the the listings booked in month 
+          in the current month with respect to the ones of 
+          the previous month. 
+          It can be null if the listings booked in month in the 
+          previous month are null.
+          This field is used for the growth score computation.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: yoy_listings_booked_in_month_growth
+        data_type: decimal
+        description: |
+          Relative increment of the listings booked in month 
+          in the current month with respect to the ones of 12
+          months ago. 
+          It can be null if the listings booked in month of 12 
+          months ago are null. 
+          This field is used for the growth score computation.
+        tests:
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: -1
+              strictly: false
+
+      - name: deal_revenue_12_months_window
+        data_type: decimal
+        description: |
+          Total aggregated revenue in GBP generated by a deal 
+          in the months from the period ranging from the 
+          aggregated_revenue_from_first_day_month to 
+          aggregated_revenue_to_first_day_month. 
+          It can be negative if the sum is negative. 
+          It cannot be null.
+        tests:
+          - not_null
+
+      - name: effective_deal_revenue_12_months_window
+        data_type: decimal
+        description: |
+          Effective aggregated revenue in GBP generated by a deal 
+          in the months from the period ranging from the 
+          aggregated_revenue_from_first_day_month to 
+          aggregated_revenue_to_first_day_month. 
+          All negative monthly revenue values are settled as 0,
+          thus this value should not be reported. 
+          It is used for the deal contribution share with respect 
+          to the global revenue. It cannot be null.
+        tests:
+          - not_null
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: effective_global_revenue_12_months_window
+        data_type: decimal
+        description: |
+          Effective aggregated revenue in GBP generated by all deals 
+          in the months from the period ranging from the 
+          aggregated_revenue_from_first_day_month to 
+          aggregated_revenue_to_first_day_month. 
+          All negative monthly revenue values are settled as 0,
+          thus this value should not be reported. 
+          It is used for the deal contribution share with respect 
+          to the global revenue. It cannot be null.
+        tests:
+          - not_null
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: deal_contribution_share_to_global_revenue
+        data_type: decimal
+        description: |
+          Represents the size of the deal in terms of revenue. In
+          other words, what's the percentage of the global revenue 
+          that can be attributed to this deal. It cannot be null.
+        tests:
+          - not_null
+          - dbt_expectations.expect_column_values_to_be_between:
+              min_value: 0
+              strictly: false
+
+      - name: deal_contribution_rank_to_global_revenue
+        data_type: integer
+        description: |
+          Represents the ordered list of deals by descending size 
+          in terms of revenue. It cannot be null. If more than one 
+          deal have the same share, the order is not under control.
+          It cannot be null.
+        tests:
+          - not_null
+
+      - name: avg_mom_growth_score
+        data_type: decimal
+        description: |
+          Represents the average score of MoM growth of created 
+          bookings, MoM growth of listings booked in month and 
+          MoM shifted by one month of revenue.
+          It indicates the tendency of growth of the deal without 
+          taking into account its revenue size. It cannot be null.
+        tests:
+          - not_null
+
+      - name: avg_yoy_growth_score
+        data_type: decimal
+        description: |
+          Represents the average score of YoY growth of created 
+          bookings, YoY growth of listings booked in month and 
+          YoY shifted by one month of revenue.
+          It indicates the tendency of growth of the deal without 
+          taking into account its revenue size. It cannot be null.
+        tests:
+          - not_null
+
+      - name: avg_growth_score
+        data_type: decimal
+        description: |
+          Represents the average score of YoY and MoM growth of created 
+          bookings, YoY and MoM growth of listings booked in month and 
+          YoY and MoM shifted by one month of revenue.
+          It indicates the tendency of growth of the deal without 
+          taking into account its revenue size. It cannot be null.
+        tests:
+          - not_null
+
+      - name: weighted_avg_growth_score
+        data_type: decimal
+        description: |
+          It's the weighted version of avg_growth_score that 
+          takes into account the client size by using the revenue 
+          contribution share of that deal to the global amount.
+          It's the main indicator towards measuring both growth 
+          (if positive) or decay (if negative) while weighting 
+          the financial impact this deal tendency can have.
+        tests:
+          - not_null
+
+      - name: categorisation_weighted_avg_growth_score
+        data_type: string
+        description: |
+          Discrete categorisation of weighted_avg_growth_score.
+          It helps easily identifying which accounts are top losers, 
+          losers, flat, winners and top winners. 
+          Currently the categorisation is based on the score itself 
+          rather than selecting a top up/down.
+        tests:
+          - not_null
+          - accepted_values:
+              values:
+                - TOP LOSER
+                - LOSER
+                - FLAT
+                - WINNER
+                - TOP WINNER
+                - UNSET