data-dwh-dbt-project/models/reporting/general/schema.yml

version: 2

models:
  - name: dates
    description: |
      A dates dimension. Each record represents one calendar day. 

      All othe columns have handy representations of the date, its subcomponents, and other relative dates.

      This table is generated with the dbt date package: https://hub.getdbt.com/calogica/dbt_date/latest/.
    columns:
      - name: date_day
        data_type: date
        description: The date this record represents. All relative dates are relative to this. All derived date components are derived from this.

      - name: prior_date_day
        data_type: date
        description: The day before date day.

      - name: next_date_day
        data_type: date
        description: The day after date day.

      - name: prior_year_date_day
        data_type: date
        description: The same day of the same month, but in the previous year. If date day is Feb 29th, this col returns Feb 28th.

      - name: prior_year_over_year_date_day
        data_type: date
        description: The day placed 365 days before the date day. Behaves a bit funny with leap years.

      - name: day_of_week
        data_type: integer
        description: The day of the week as a number, were Monday is 1 and Sunday is 7.

      - name: day_of_week_name
        data_type: text
        description: The full name of the day of the week.

      - name: day_of_week_name_short
        data_type: text
        description: The day of the week as a 3 digit shortened version.

      - name: day_of_month
        data_type: integer
        description: The day of the month as a number.

      - name: day_of_year
        data_type: integer
        description: The day of the year as a number, where January 1st is 1 and December 31st is 365/366.

      - name: week_start_date
        data_type: date
        description: |
          The full date for the first day of the week of date day. 

          It considers Sunday to be the first day of the week.

      - name: week_end_date
        data_type: date
        description: |
          The full date for the last day of the week of date day. 

          It considers Saturday to be the last day of the week.

      - name: prior_year_week_start_date
        data_type: date
        description: Same as week_start_date, but for the same date day in the previous year.

      - name: prior_year_week_end_date
        data_type: date
        description: Same as week_end_date, but for the same date day in the previous year.

      - name: week_of_year
        data_type: integer
        description: The week of the year as a number, where the first week is 1 and the last week is 52/53.

      - name: iso_week_start_date
        data_type: date
        description: |
          The full date for the first day of the week of date day, according to ISO specs. 

          It considers Monday to be the first day of the week.

          Read more here: https://en.wikipedia.org/wiki/ISO_week_date

      - name: iso_week_end_date
        data_type: date
        description: |
          The full date for the last day of the week of date day, according to ISO specs. 

          It considers Sunday to be the last day of the week.

          Read more here: https://en.wikipedia.org/wiki/ISO_week_date

      - name: prior_year_iso_week_start_date
        data_type: date
        description: "Read more here: https://en.wikipedia.org/wiki/ISO_week_date"

      - name: prior_year_iso_week_end_date
        data_type: date
        description: "Read more here: https://en.wikipedia.org/wiki/ISO_week_date"

      - name: iso_week_of_year
        data_type: integer
        description: "Read more here: https://en.wikipedia.org/wiki/ISO_week_date"

      - name: prior_year_week_of_year
        data_type: integer
        description: ""

      - name: prior_year_iso_week_of_year
        data_type: integer
        description: "Read more here: https://en.wikipedia.org/wiki/ISO_week_date"

      - name: month_of_year
        data_type: integer
        description: The month date day belongs to as a number (1 for Jan, 12 for Dec).

      - name: month_name
        data_type: text
        description: The month date day belongs to in English.

      - name: month_name_short
        data_type: text
        description: The month date day belongs to as a 3 digit shortened version.

      - name: month_number_name
        data_type: text
        description: The month date number with leading zero and full month name (e.g., 01-January, 02-February).

      - name: month_number_name_short
        data_type: text
        description: The month date number with leading zero and abbreviated month name (e.g., 01-Jan, 02-Feb).

      - name: month_start_date
        data_type: date
        description: The full date for the first day of the month.

      - name: month_end_date
        data_type: date
        description: The full date for the last day of the month.

      - name: prior_year_month_start_date
        data_type: date
        description: The full date for the first day of the same month last year.

      - name: prior_year_month_end_date
        data_type: date
        description: The full date for the last day of the same month last year.

      - name: quarter_of_year
        data_type: integer
        description: The quarter date day belongs to as a number (1 for Q1, 4 for Q4).

      - name: quarter_start_date
        data_type: date
        description: The full date for the first date of the quarter.

      - name: quarter_end_date
        data_type: date
        description: The full date for the last date of the quarter.

      - name: year_number
        data_type: integer
        description: The year date day belongs to as a number.

      - name: year_start_date
        data_type: date
        description: The full date for the first day of the year.

      - name: year_end_date
        data_type: date
        description: The full date for the last day of the year.

  - name: daily_currency_exchange_rates
    config:
      grants:
        select: ["billingdb_reader"]
    description:
      This model holds a lot of data on currency exchange rates.  The time
      granularity is daily. Each record holds a currency pair for a specific
      day, source and version.

      Actual rates are sourced from xe.com data. The `guessed` and `forecast`
      versions are built by simply 'pushing'  the first/last exchange rate on
      record. Basically, wherever we don't have data for a date, we pick the
      closest actual data point that comes from xe.com. Bear in mind this means
      that `forecast` version records will change on a daily basis as actual
      data moves forwards, meaning you shouldn't assume your money amounts
      converted in the future should always stay put.

      Note that, given the dimensionality, getting a simple time series for a
      currency pair will require a bit of filtering.

      Reverse rates are explicit. This means that, for any given day and any
      given currency pair, you will find two records with opposite from/to
      positions. So, for 2024-01-01, you will find both a EUR->USD record and a
      USD->EUR record with the opposite rate (1/rate).
    columns:
      - name: id_exchange_rate
        data_type: text
        description: A unique ID for the record, derived from concatenating the
          currencies, date, source and version. Currency order is relevant
          (EURUSD != USDEUR).
        data_tests:
          - not_null
          - unique
      - name: from_currency
        data_type: character
        description: The source currency, represented as an ISO 4217 code.
        data_tests:
          - not_null
      - name: to_currency
        data_type: character
        description: The target currency, represented as an ISO 4217 code.
        data_tests:
          - not_null
      - name: rate
        data_type: numeric
        description: >-
          The exchange rate, represented as the units of the target currency
          that one unit of source currency gets you. So, from_currency=USD to
          to_currency=PLN with rate=4.2 should be read as '1 US Dollar buys me
          4.2 Polish Zlotys'.

          For same currency pairs (EUR to EUR, USD to USD, etc). The rate will
          always be one.

          The rate can be smaller than one, but can't be negative.
        data_tests:
          - not_negative_or_zero
          - not_null
      - name: rate_date_utc
        data_type: date
        description: The date in which the rate record is relevant.
        data_tests:
          - not_null
      - name: source
        data_type: text
        description:
          Where is the data coming from. Records that are composed from
          making assumptions on real data will contain `_inferred`.
      - name: rate_version
        data_type: text
        description:
          The version of the rate. This can be one of `actual` (the rate is a
          reality fact), `forecast` (the rate sits in the future and is a guess
          in nature) or `guess` (the rate sits in the past and is a guess in
          nature). Note that one currency pair can have multiple rate versions
          on the same date.
        data_tests:
          - accepted_values:
              values:
                - guess
                - actual
                - forecast
          - not_null
      - name: updated_at_utc
        data_type: timestamp with time zone
        description:
          For external sources, this will be the point in time when the
          information was obtained from them. For stuff we make up here in the
          DWH, this will be the point in time when we made the assumption.
        data_tests:
          - not_null

  - name: simple_exchange_rates
    description: >-
      A simplified vision of exchange rates, derived from
      `int_daily_currency_exchange_rates`. Come here if you don't want to
      understand nuances and complexities and just want to convert rates.

      The time granularity is daily. Each record holds a currency pair for a
      specific day. You will only find one conversion rate per currency pair and
      date.
    data_tests:
      - dbt_utils.unique_combination_of_columns:
          combination_of_columns:
            - from_currency
            - to_currency
            - rate_date_utc
    columns:
      - name: from_currency
        data_type: character
        description: The source currency, represented as an ISO 4217 code.
        data_tests:
          - not_null
      - name: to_currency
        data_type: character
        description: The source currency, represented as an ISO 4217 code.
        data_tests:
          - not_null
      - name: rate
        data_type: numeric
        description: The target currency, represented as an ISO 4217 code.
        data_tests:
          - not_null
      - name: rate_date_utc
        data_type: date
        description: The date in which the rate record is relevant.
        data_tests:
          - not_null
      - name: updated_at_utc
        data_type: timestamp with time zone
        description:
          For external sources, this will be the point in time when the
          information was obtained from them. For stuff we make up here in the
          DWH, this will be the point in time when we made the assumption.
        data_tests:
          - not_null

  - name: mtd_aggregated_metrics
    description: |
      This model aggregates the historic information of our business by providing
      different metrics computed at global and dimension level.
      It's the main source of information for the Main KPIs reporting, specifically
      on the MTD (Month To Date) and the Monthly Overview.

    data_tests:
      - dbt_utils.unique_combination_of_columns:
          combination_of_columns:
            - date
            - metric
            - dimension
            - dimension_value

    columns:
      - name: year
        data_type: int
        description: Year number of the given date.
        data_tests:
          - not_null

      - name: month
        data_type: int
        description: Month number of the given date.
        data_tests:
          - not_null

      - name: day
        data_type: int
        description: Day monthly number of the given date.
        data_tests:
          - not_null

      - name: is_end_of_month
        data_type: boolean
        description: Is end of month, 1 for yes, 0 for no.
        data_tests:
          - not_null

      - name: is_current_month
        data_type: boolean
        description: |
          Checks if the date is within the current executed month, 
          1 for yes, 0 for no.
        data_tests:
          - not_null

      - name: is_end_of_month_or_yesterday
        data_type: boolean
        description: |
          Checks if the date is end of month or yesterday, 
          1 for yes, 0 for no.
        data_tests:
          - not_null

      - name: first_day_month
        data_type: date
        description: |
          First day of the month corresponding to the date field. 
          It comes from int_dates_mtd logic.
        data_tests:
          - not_null

      - name: date
        data_type: date
        description: |
          Main date for the computation, that is used for filters. 
          It comes from int_dates_mtd logic.
        data_tests:
          - not_null
          - latest_date_is_yesterday

      - name: dimension
        data_type: string
        description: |
          The dimension or granularity of the metrics. Keep in mind that
          in this reporting model this field corresponds to the 
          dimension_display; this is, the name of the dimension for 
          displaying purposes.

        data_tests:
          - not_null

      - name: dimension_value
        data_type: string
        description: The value or segment available for the selected dimension.
        data_tests:
          - not_null

      - name: previous_year_date
        data_type: date
        description: |
          Corresponds to the date of the previous year, with respect to the field date. 
          It comes from int_dates_mtd logic. It's only displayed for information purposes,
          should not be needed for reporting.

      - name: metric
        data_type: text
        description: Name of the business metric.
        data_tests:
          - not_null

      - name: order_by
        data_type: integer
        description: |
          Order for displaying purposes. Null values are accepted, but keep
          in mind that then there's no default controlled display order.

      - name: number_format
        data_type: text
        description: Allows for grouping and formatting for displaying purposes.
        data_tests:
          - accepted_values:
              values:
                [
                  "integer",
                  "percentage",
                  "currency_gbp",
                  "converted_metric_currency_gbp",
                ]

      - name: value
        data_type: numeric
        description: |
          Numeric value (integer or decimal) that corresponds to the MTD computation of the metric
          at a given date. Note that if the month is not in progress, then this value corresponds
          to the monthly figure.

      - name: previous_year_value
        data_type: numeric
        description: |
          Numeric value (integer or decimal) that corresponds to the MTD computation of the metric
          on the previous year at a given date.

      - name: relative_increment
        data_type: numeric
        description: |
          Numeric value that corresponds to the relative increment between value and previous year value,
          following the computation: value / previous_year_value - 1.

      - name: relative_increment_with_sign_format
        data_type: numeric
        description: |
          Relative_increment value multiplied by -1 in case this metric's growth doesn't have a
          positive impact for Truvi, otherwise is equal to relative_increment.
          This value is specially created for formatting in PBI

  - name: monthly_aggregated_metrics_history_by_deal
    description: |
      This model aggregates the monthly historic information regarding the different metrics computed
      at deal level. The primary source of data is the `int_monthly_XXXXX_history_by_deal`
      model which contain the raw metrics data per source. 

      This table is used to provide "By Deal" metrics in the Business Overview reporting.
      Unlike the mtd_aggregated_metrics, this model does not abstract each metric, since
      no comparison versus last year is performed. In short, it just gathers the information stored
      in the abovementioned models.

      To keep in mind: aggregating the information of this model will not necessarily result into
      the int_mtd_aggregated_metrics because 1) the mtd version contains more computing dates
      than the by deal version, the latest being a subset of the first, and 2) the deal based model
      enforces that a booking/guest journey/listing/etc has a host with a deal assigned, which is
      not necessarily the case.

    data_tests:
      - dbt_utils.unique_combination_of_columns:
          combination_of_columns:
            - date
            - id_deal

    columns:
      - name: date
        data_type: date
        description: The last day of the month for historic metrics.
        data_tests:
          - not_null

      - name: id_deal
        data_type: character varying
        description: Id of the deal associated to the host.
        data_tests:
          - not_null

      - name: client_type
        data_type: string
        description: |
          Type of client. It can be either PLATFORM or API.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - PLATFORM
                - API

      - name: business_scope
        data_type: string
        description: |
          Business scope identifying the metric source.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - "Old Dash"
                - "New Dash"
                - "API"
                - "UNSET"

      - name: main_deal_name
        data_type: string
        description: |
          Main name for this ID deal.
        data_tests:
          - not_null

      - name: main_billing_country_iso_3_per_deal
        data_type: string
        description: |
          ISO 3166-1 alpha-3 main country code in which the Deal is billed.
          In some cases it's null.

      - name: year
        data_type: int
        description: year number of the given date.
        data_tests:
          - not_null

      - name: month
        data_type: int
        description: month number of the given date.
        data_tests:
          - not_null

      - name: day
        data_type: int
        description: day monthly number of the given date.
        data_tests:
          - not_null

      - name: host_resolution_amount_paid_per_created_booking
        data_type: decimal
        description: |
          Host resolution amount paid divided by the number of
          created bookings in the time window. It can be null if
          no resolution payments were made by the host. 
          It can be negative or positive.

      - name: host_resolution_payment_per_created_booking_ratio
        data_type: decimal
        description: |
          Ratio of Host resolution payment count divided by the
          number of created bookings in the time window. It can be null
          if no resolution payments were made by the host.
          It is capped between -1 and 1.
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: -1
              max_value: 1
              strictly: false

      - name: revenue_retained_ratio
        data_type: decimal
        description: |
          Ratio of Revenue Retained divided by Total Revenue.
          It is capped between -1 and 1. It can be Null
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: -1
              max_value: 1
              strictly: false

      - name: revenue_retained_post_resolutions_ratio
        data_type: decimal
        description: |
          Ratio of Revenue Retained Post-Resolutions 
          divided by Total Revenue.
          It is capped between -1 and 1. It can be Null
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: -1
              max_value: 1
              strictly: false

  - 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.

    data_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.
        data_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.
        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: client_type
        data_type: string
        description: |
          Type of client. It can be either PLATFORM or API.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - PLATFORM
                - API

      - name: main_deal_name
        data_type: string
        description: |
          Main name for a Deal, representing the client.
        data_tests:
          - not_null

      - name: has_active_pms
        data_type: boolean
        description: |
          Does the deal have an active associated PMS.
        data_tests:
          - not_null

      - name: active_pms_list
        data_type: string
        description: |
          Name of the active PMS associated with the deal. It can have more than
          one PMS associated with it. It can be null if it doesn't have any PMS associated.

      - 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: deal_hubspot_stage
        data_type: string
        description: |
          Current hubspot stage for a given deal.

      - name: account_manager
        data_type: string
        description: |
          Current Account Manager in charge of a given deal, according
          to Hubspot.

      - name: live_date_utc
        data_type: date
        description: |
          Date in which the account has gone live, according to Hubspot.

      - name: cancellation_date_utc
        data_type: date
        description: |
          Date in which the account has been offboarded, according to 
          Hubspot.

      - 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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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. 
          If more than one deal have the same share, the order is 
          not under control.
          It cannot be null.
        data_tests:
          - not_null

      - name: deal_created_bookings_12_months_window
        data_type: integer
        description: |
          Total created bookings 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 cannot be null.
        data_tests:
          - not_null
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: global_created_bookings_12_months_window
        data_type: integer
        description: |
          Total created bookings generated by any deal 
          in the months from the period ranging from the 
          aggregated_revenue_from_first_day_month to 
          aggregated_revenue_to_first_day_month. 
          It is used for the deal contribution share with respect 
          to the global created bookings. It cannot be null.
        data_tests:
          - not_null
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: deal_contribution_share_to_global_created_bookings
        data_type: decimal
        description: |
          Represents the size of the deal in terms of created bookings. 
          In other words, what's the percentage of the global created 
          bookings that can be attributed to this deal. 
          It cannot be null.
        data_tests:
          - not_null
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: deal_contribution_rank_to_global_created_bookings
        data_type: integer
        description: |
          Represents the ordered list of deals by descending size 
          in terms of created bookings. 
          If more than one deal have the same share, the order is 
          not under control.
          It cannot be null.
        data_tests:
          - not_null

      - name: deal_avg_listings_booked_in_month_12_months_window
        data_type: decimal
        description: |
          Average listings booked in month 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 cannot be null.
        data_tests:
          - not_null
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: global_avg_listings_booked_in_month_12_months_window
        data_type: decimal
        description: |
          Sum of the average listings booked in month by 
          any deal in the months from the period ranging from the 
          aggregated_revenue_from_first_day_month to 
          aggregated_revenue_to_first_day_month. 
          It is used for the deal contribution share with respect 
          to the global average listings booked in month. 
          It cannot be null.
        data_tests:
          - not_null
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: deal_contribution_share_to_global_avg_listings_booked_in_month
        data_type: decimal
        description: |
          Represents the size of the deal in terms of average listings 
          booked in month. 
          In other words, what's the percentage of the global average listings
          booked in month that can be attributed to this deal. 
          It cannot be null.
        data_tests:
          - not_null
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: deal_contribution_rank_to_global_avg_listings_booked_in_month
        data_type: decimal
        description: |
          Represents the ordered list of deals by descending size 
          in terms of average listings booked in month. 
          If more than one deal have the same share, the order is 
          not under control.
          It cannot be null.
        data_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.
        data_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.
        data_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.
        data_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.
        data_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.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - MAJOR DECLINE
                - DECLINE
                - FLAT
                - GAIN
                - MAJOR GAIN
                - UNSET

  - name: new_dash_booking_summary
    description: |
      This model contains enriched information aggregated at Booking level regarding
      the services that are applied within a Booking, only for users in New Dash.
      Specifically, contains both Booking and Services attributes (aggregated), as well 
      as the total price in GBP at this specific moment in time. In other words, 
      it's the snapshot of the current status of the Booking. 
      It's a subset of all bookings since it only applies to bookings that come from 
      hosts that have been migrated into the New Dash.

    columns:
      - name: id_booking
        data_type: bigint
        description: |
          The identifier of the booking. Acts as Primary Key to this table.
          Cannot be null.
        data_tests:
          - not_null
          - unique

      - name: has_verification_request
        data_type: boolean
        description: |
          Flag to identify if the booking has a verification request or not.
          Cannot be null.
        data_tests:
          - not_null

      - name: id_deal
        data_type: string
        description: |
          Unique identifier of the account. It cannot be null.
        data_tests:
          - not_null

      - name: main_billing_country
        data_type: string
        description: |
          ISO 3166-1 alpha-3 main country code in which the Deal is billed.

      - name: main_deal_name
        data_type: string
        description: |
          Main name for this ID deal, according to some logic from 
          backend (core) data.
          It's a clean version of the most repeated name within the 
          user tables in the fields of first_name, last_name and company name. 
          This field should be modified at the moment we have
          a proper way to retrieve a common account name per deal.
          It can contain duplicates.
        data_tests:
          - not_null

      - name: hubspot_deal_name
        data_type: string
        description: |
          Name of the deal according to Hubspot. Preferred over main_deal_name.

      - name: account_manager
        data_type: string
        description: |
          The name of the account manager that is currently taking care of this
          deal.

      - name: booking_status
        data_type: string
        description: |
          The current status of the booking. Cannot be null.
        data_tests:
          - not_null

      - name: program_name
        data_type: string
        description: |
          The name of the program, or product bundle, applied to the booking. 
          Cannot be null.
        data_tests:
          - not_null

      - name: booking_created_date_utc
        data_type: date
        description: |
          Date of when the Booking record was created in the Backend.
          Cannot be null.
        data_tests:
          - not_null

      - name: booking_check_in_date_utc
        data_type: timestamp
        description: |
          Date of the Check-in of the Booking.
          Cannot be null.
        data_tests:
          - not_null

      - name: booking_check_out_date_utc
        data_type: date
        description: |
          Date of the Check-out of the Booking.
        data_tests:
          - not_null

      - name: booking_number_of_nights
        data_type: integer
        description: |
          Number of nights between Check-in date and Check-out date.

      - name: host_currency_code
        data_type: string
        description: |
          Iso 4217 currency code for the account of the Host.
          It can be null.

      - name: new_dash_version
        data_type: string
        description: |
          Specifies the New Dash Version in which these users were 
          moved or joined.
        data_tests:
          - not_null

      - name: user_in_new_dash_since_date_utc
        data_type: date
        description: |
          The effective date since the user can be considered in New Dash. If the user 
          has moved from Old Dash, it will be the date of new_dash_move_at_utc. 
          If not, it will correspond to the date of joined_at_utc.

      - name: booking_total_price_in_gbp
        data_type: decimal
        description: |
          Identifies the current total price of the booking by adding up the 
          prices of each service applied to this booking, converted in GBP. 
          Can be null. Can vary over time depending on the service status, 
          payments, etc, as well as it can vary over time until the chargeable 
          date due to the currency rate estimation in the future.

      - name: service_first_chargeable_date_utc
        data_type: date
        description: |
          Identifies the first moment in time in which the first 
          service applied to this booking is supposed to be charged.

      - name: service_last_chargeable_date_utc
        data_type: date
        description: |
          Identifies the last moment in time in which the last 
          service applied to this booking is supposed to be charged.

      - name: number_of_applied_services
        data_type: integer
        description: |
          Total number of Services applied to this Booking.

      - name: number_of_applied_upgraded_services
        data_type: integer
        description: |
          Total number of Services different from Basic Screening 
          applied to this Booking.

      - name: is_booking_chargeable
        data_type: boolean
        description: |
          Flag to identify it the Booking is chargeable or not.
          In essence, it solves the question: are we supposed to get 
          money out of this booking, or not?
          To be considered as chargeable, a chargeable date needs to exist 
          as well as the total price converted to GBP needs to be strictly
          greater than 0. The fact that a booking is not chargeable does
          not necessarily mean that it won't be in the future. Similarly, if 
          the booking is chargeable it does not necessarily mean that is actually
          charged. It cannot be null.
        data_tests:
          - not_null

      - name: is_booking_cancelled
        data_type: boolean
        description: |
          Flag to identify if the booking has been cancelled or not.

      - name: has_upgraded_services
        data_type: boolean
        description: |
          Flag to identify if the booking has any service different from
          Basic Screening or not.

      - name: has_screening_service_business_type
        data_type: boolean
        description: |
          Flag to identify if the booking contains any Screening service
          or not.

      - name: has_upgraded_screening_service_business_type
        data_type: boolean
        description: |
          Flag to identify if the booking contains any Screening services
          different from Basic Screening.

      - name: has_deposit_management_service_business_type
        data_type: boolean
        description: |
          Flag to identify if the booking contains any Deposit 
          Management service or not.

      - name: has_protection_service_business_type
        data_type: boolean
        description: |
          Flag to identify if the booking contains any Protection 
          service or not.

  - name: monthly_aggregated_metrics_history_by_deal_by_time_window
    description: |
      This model aggregates monthly historic metrics for deals over different time windows.
      It provides insights into bookings, listings, revenue, retained revenue and 
      additional metrics.
      The data is segmented by deal and time window for detailed analysis.

    data_tests:
      - dbt_utils.unique_combination_of_columns:
          combination_of_columns:
            - date
            - id_deal
            - time_window

    columns:
      - name: date
        data_type: date
        description: |
          The last day of the month or yesterday for historic metrics.
          It's the same date as for KPIs related models.
        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: id_deal
        data_type: character varying
        description: Id of the deal associated to the host.
        data_tests:
          - not_null

      - name: time_window
        data_type: character varying
        description: |
          Identifier of the time window used for the aggregation of the metrics.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - All History
                - Previous 12 months
                - Previous 6 months
                - Previous 3 months
                - Previous month

      - name: client_type
        data_type: string
        description: |
          Type of client. It can be either PLATFORM or API.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - PLATFORM
                - API

      - name: business_scope
        data_type: string
        description: |
          Business scope identifying the metric source.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - "Old Dash"
                - "New Dash"
                - "API"
                - "UNSET"

      - name: metric_from_date
        data_type: date
        description: |
          The first day of the month corresponding to the lower bound
          range in which the metric is computed. It can be null if 
          there's no previous history for that deal. It can vary from 
          deal to deal depending on the number of months the deal has 
          been active.

      - name: metric_to_date
        data_type: date
        description: |
          The first day of the month corresponding to the upper bound
          range in which the metric is computed. It can be null if 
          there's no previous history for that deal.

      - name: main_deal_name
        data_type: string
        description: |
          Main name for this ID deal.
        data_tests:
          - not_null

      - name: has_active_pms
        data_type: boolean
        description: |
          Does the deal have an active associated PMS.
        data_tests:
          - not_null

      - name: active_pms_list
        data_type: string
        description: |
          Name of the active PMS associated with the deal. It can have more than
          one PMS associated with it. It can be null if it doesn't have any PMS associated.

      - name: active_accommodations_per_deal_segmentation
        data_type: string
        description: |
          Segment value based on the number of listings booked in 12 months 
          for a given deal and date.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - "0"
                - "01-05"
                - "06-20"
                - "21-60"
                - "61+"
                - "UNSET"

      - name: main_billing_country_iso_3_per_deal
        data_type: string
        description: |
          ISO 3166-1 alpha-3 main country code in which the Deal is billed.
          In some cases it's null.

      - name: deal_lifecycle_state
        data_type: string
        description: |
          Lifecycle state of the deal.

      - name: deal_hubspot_stage
        data_type: string
        description: |
          Hubspot stage of the deal.
          In some cases it's null.

      - name: account_manager
        data_type: string
        description: |
          Account manager of the deal.
          In some cases it's null.

      - name: live_date_utc
        data_type: date
        description: |
          Date when the deal went live according to 
          Hubspot. In some cases it's null.

      - name: cancellation_date_utc
        data_type: date
        description: |
          Date when the deal was cancelled according to 
          Hubspot. It can be null if the deal has never 
          churned.

      - name: months_between_live_and_churn
        data_type: integer
        description: |
          Number of months between the live date and the 
          churn date.
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: last_contacted_date_utc
        data_type: date
        description: |
          Date when the deal was last contacted according to 
          Hubspot.

      - name: days_between_last_contacted_and_churn
        data_type: integer
        description: |
          Number of days between the last contacted date 
          and the churn date.
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: amount_times_contacted
        data_type: integer
        description: |
          Number of times the deal was contacted according 
          to Hubspot.

      - name: cancellation_category
        data_type: text
        description: Categorization as to why they cancelled the account

      - name: cancellation_details
        data_type: text
        description: Free text with additional comments on why they cancelled the account

      - name: is_churning
        data_type: boolean
        description: |
          Flag to identify if the deal is churning or not.

      - name: churn_reason
        data_type: string
        description: |
          Reason why the deal is churning.
        data_tests:
          - accepted_values:
              values:
                - "INACTIVITY"
                - "ACCOUNT CANCELLATION"

      - name: created_bookings
        data_type: integer
        description: |
          Total amount of bookings created by the deal 
          in the time window. It can be null if no bookings 
          were created.
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: listings_booked_in_month
        data_type: decimal
        description: |
          Average amount of listings booked in month by the deal 
          in the time window. It can be null if no listings 
          were booked.
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: total_revenue_in_gbp
        data_type: decimal
        description: |
          Total revenue in GBP generated by the deal in the 
          time window. It can be null if no revenue was generated.
          It can be negative.

      - name: revenue_retained_in_gbp
        data_type: decimal
        description: |
          Total revenue in GBP retained by the deal in the 
          time window, post host takeaway waivers. 
          It can be null if no revenue was retained.
          It can be negative.

      - name: waiver_paid_back_to_host_in_gbp
        data_type: decimal
        description: |
          Total amount of waivers paid back to the host in GBP 
          in the time window. It can be null if no waivers were 
          paid back. It's displayed as a negative value.

      - name: invoiced_revenue_in_gbp
        data_type: decimal
        description: |
          Total amount of revenue in GBP invoiced to the host 
          in the time window. It considers both Operator revenue as
          well as APIs revenue. It can be null if no revenue was 
          invoiced to the host. It can be negative.

      - name: guest_payments_in_gbp
        data_type: decimal
        description: |
          Total amount of payments in GBP made by the guest 
          in the time window. It can be null if no payments 
          were made by the guest. It can be negative.
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: guest_revenue_retained_in_gbp
        data_type: decimal
        description: |
          Total amount of revenue in GBP retained by the deal 
          from the guest in the time window, post host takeaway waivers.
          It can be null if no revenue was retained from the guest. 
          It can be negative.

      - name: host_resolution_payment_count
        data_type: integer
        description: |
          Total amount of resolution payments made to the host 
          in the time window. It can be null if no resolution 
          payments were made by the host.
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: host_resolution_amount_paid_in_gbp
        data_type: decimal
        description: |
          Total amount of resolution payments made to the host 
          in GBP in the time window. It can be null if no resolution 
          payments were made by the host. It can be negative.
          It's displayed as a negative value. In some extreme 
          cases, it can be higher than 0.

      - name: revenue_retained_post_resolutions_in_gbp
        data_type: decimal
        description: |
          Total amount of revenue in GBP retained by the deal 
          post waiver payouts and resolution payouts in the time window. 
          It can be null if no revenue was retained post resolution payments.
          It can be negative, thus indicating that we are losing money.
  - name: edeposit_and_athena_verifications
    description:
      "This table holds records on verifications for Guesty and Edeposit bookings.
      It contains details on validations checked on the guests, guest information
      and some booking details like checkin-checkout date or the status of the verification.
      The id values found here are completely unrelated to the ones found in Core DWH.

      Note that id_verifications and booking_id should normally be 1 to 1.
      Though there are exception, the API will accept a duplicate booking and the users
      will be charged for it. A duplicate would return a unique id_verification."
    columns:
      - name: id_verification
        data_type: text
        description: "unique Superhog generated id for this verification"
        data_tests:
          - unique
          - not_null

      - name: id_booking
        data_type: text
        description: "unique Superhog generated id for a booking.
          note that this could be duplicated and both will be charged,
          it's up to the user to no generate duplicate verifications"

      - name: id_user_partner
        data_type: text
        description: "unique Superhog generated id for partner"
        data_tests:
          - not_null

      - name: id_accommodation
        data_type: text
        description: "unique Superhog generated id for a listing"

      - name: version
        data_type: text
        description: "value to identify if it is Guesty (V1) or E-deposit (V2)"
        data_tests:
          - accepted_values:
              values:
                - V1
                - V2

      - name: verification_source
        data_type: text
        description: "source of the verification for the booking"
        data_tests:
          - accepted_values:
              values:
                - Guesty
                - Edeposit

      - name: verification_status
        data_type: text
        description: "status of the verification"

      - name: nightly_fee_local
        data_type: double precision
        description: "fee in local currency charged per night"

      - name: number_nights
        data_type: integer
        description: "number of nights for the booking"

      - name: total_fee_local
        data_type: double precision
        description: "total fee in local currency for the booking"

      - name: email_flag
        data_type: text
        description: "screening result for email"

      - name: phone_flag
        data_type: text
        description: "screening result for phone"

      - name: watch_list
        data_type: text
        description: "screening result of the guest"

      - name: channel
        data_type: text
        description: ""

      - name: checkin_at_utc
        data_type: timestamp without time zone
        description: "Timestamp of checkin for the booking"

      - name: checkin_date_utc
        data_type: date
        description: "Date of checkin for the booking"

      - name: checkout_at_utc
        data_type: timestamp without time zone
        description: "Timestamp of checkout for the booking"

      - name: checkout_date_utc
        data_type: date
        description: "Date of checkout for the booking"

      - name: is_cancelled
        data_type: boolean
        description: ""

      - name: cancelled_at_utc
        data_type: timestamp without time zone
        description: "Timestamp of cancellation of the booking"

      - name: cancelled_date_utc
        data_type: date
        description: "Date of cancellation for the booking"

      - name: user_email
        data_type: text
        description: ""

      - name: guest_email
        data_type: text
        description: ""

      - name: guest_last_name
        data_type: text
        description: ""

      - name: guest_first_name
        data_type: text
        description: ""

      - name: guest_telephone
        data_type: text
        description: ""

      - name: company_name
        data_type: text
        description: ""

      - name: property_manager_name
        data_type: text
        description: ""

      - name: property_manager_email
        data_type: text
        description: ""

      - name: listing_name
        data_type: text
        description: ""

      - name: listing_address
        data_type: text
        description: ""

      - name: listing_town
        data_type: text
        description: ""

      - name: listing_country
        data_type: text
        description: ""

      - name: listing_postcode
        data_type: text
        description: ""

      - name: pets_allowed
        data_type: boolean
        description: ""

      - name: level_of_protection_amount
        data_type: integer
        description: ""

      - name: level_of_protection_currency
        data_type: text
        description: ""

      - name: status_updated_at_utc
        data_type: timestamp without time zone
        description: "Timestamp when status was last updated"

      - name: status_updated_date_utc
        data_type: date
        description: "Date of last status update of the verification"

      - name: updated_at_utc
        data_type: timestamp without time zone
        description: "Timestamp of last updated of the verification"

      - name: updated_date_utc
        data_type: date
        description: "Date of last update of the verification"

      - name: athena_creation_at_utc
        data_type: timestamp without time zone
        description:
          "Athena timestamp referring to when the booking was created.
          It's provided by Guesty, but is not mandatory.
          In case of doubt use created_at_utc or created_date_utc fields"

      - name: athena_creation_date_utc
        data_type: date
        description: "Athena date referring to when the booking was created.
          It's provided by Guesty, but is not mandatory.
          In case of doubt use created_at_utc or created_date_utc fields"

      - name: created_at_utc
        data_type: timestamp without time zone
        description: "Timestamp of creation of the verification in the system"

      - name: created_date_utc
        data_type: date
        description: "Date of creation of the verification in the system"

  - name: deals_consolidation
    description: |
      "This table contains all deal ids from different sources used in Superhog. 
      It contains the source (Hubspot, Xero or Core), the id_deal and the name"
    columns:
      - name: id_deal
        data_type: character varying
        description: "Unique ID for this deal."
        data_tests:
          - unique
          - not_null

      - name: core_company_name
        data_type: character varying
        description: "Company name of the deal as shown in Core."

      - name: core_company_name_count
        data_type: integer
        description: "Count of distinct names the deal has in Core.
          It might be the case that a deal has ony NULL value for a name,
          so the count will be 0"
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: hubspot_deal_name
        data_type: character varying
        description: "Name of the deal as shown in Hubspot."

      - name: hubspot_deal_name_count
        data_type: integer
        description: "Count of distinct names the deal has in Hubspot.
          It might be the case that a deal has ony NULL value for a name,
          so the count will be 0"
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: xero_contact_name
        data_type: character varying
        description: "Contact name of the deal as shown in Xero."

      - name: xero_contact_name_count
        data_type: integer
        description: "Count of distinct names the deal has in Xero.
          It might be the case that a deal has ony NULL value for a name,
          so the count will be 0"
        data_tests:
          - dbt_expectations.expect_column_values_to_be_between:
              min_value: 0
              strictly: false

      - name: is_deal_in_core
        data_type: boolean
        description: "Flag to indicate if the deal is in Core."

      - name: is_deal_in_hubspot
        data_type: boolean
        description: "Flag to indicate if the deal is in Hubspot."

      - name: is_deal_in_xero
        data_type: boolean
        description: "Flag to indicate if the deal is in Xero."

  - name: ytd_mtd_aggregated_main_metrics_overview
    description: |
      This model provides a high-level overview of the main metrics for the month-to-date 
      and financial year-to-date periods. Data is aggregated at metric level, and provides 
      evolutions current month MTD vs. previous month EOM, current month MTD vs. previous 
      year MTD and current YTD vs. previous YTD.

    data_tests:
      - dbt_utils.unique_combination_of_columns:
          combination_of_columns:
            - date
            - dimension
            - dimension_value
            - metric_name
      - dbt_utils.unique_combination_of_columns:
          combination_of_columns:
            - date
            - dimension
            - dimension_value
            - id_metric

    columns:
      - name: date
        data_type: date
        description: The date for the month-to-date and year-to-date metrics.
        data_tests:
          - not_null

      - name: dimension
        data_type: string
        description: The dimension or granularity of the metrics.
        data_tests:
          - accepted_values:
              values:
                - global

      - 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: The first day of the month associated with the data.
        data_tests:
          - not_null

      - name: calendar_year
        data_type: integer
        description: The calendar year associated with the data.
        data_tests:
          - not_null

      - name: financial_year
        data_type: integer
        description: The financial year associated with the data.
        data_tests:
          - not_null

      - name: previous_year_date
        data_type: date
        description: |
          The equivalent date in the previous year. It can be null if the 
          metric is not available in the previous year

      - name: id_metric
        data_type: integer
        description: |
          Unique ID for this metric. It is preferable to use this ID when 
          building a report to ensure changes in the metric name do not
          affect the report.
        data_tests:
          - not_null

      - name: metric_name
        data_type: string
        description: |
          Name of the metric. It is preferable to use the ID of the metric
          when building a report to ensure changes in the metric name do not
          affect the report.
        data_tests:
          - not_null

      - name: number_format
        data_type: string
        description: |
          Number format to display the metric in the report.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - INTEGER
                - PERCENTAGE_2_DECIMALS
                - CURRENCY_GBP_INTEGER
                - CURRENCY_GBP_1_DECIMAL

      - name: is_latest_date
        data_type: integer
        description: |
          Flag to indicate if it's the latest consolidated information for this metric. 
          Keep in mind that this can be different depending on the metric, as the invoicing 
          cycle limits the availability of the latest data for some metrics.
        data_tests:
          - not_null

      - name: current_month_mtd
        data_type: numeric
        description: |
          Value of the metric for the current month MTD.

      - name: previous_month_eom
        data_type: numeric
        description: |
          Value of the metric for the previous month EOM.

      - name: previous_year_mtd
        data_type: numeric
        description: |
          Value of the metric for the previous year MTD.

      - name: current_year_ytd
        data_type: numeric
        description: |
          Value of the metric for the current year YTD.

      - name: previous_year_ytd
        data_type: numeric
        description: |
          Value of the metric for the previous year YTD.

      - name: diff_current_month_mtd_vs_previous_month_eom
        data_type: numeric
        description: |
          Difference between the current month MTD and the previous month EOM.

      - name: diff_current_month_mtd_vs_previous_year_mtd
        data_type: numeric
        description: |
          Difference between the current month MTD and the previous year MTD.

      - name: diff_current_ytd_vs_previous_ytd
        data_type: numeric
        description: |
          Difference between the current year YTD and the previous year YTD.

      - name: rel_diff_current_month_mtd_vs_previous_month_eom
        data_type: numeric
        description: |
          Relative difference between the current month MTD and the previous month EOM.

      - name: rel_diff_current_month_mtd_vs_previous_year_mtd
        data_type: numeric
        description: |
          Relative difference between the current month MTD and the previous year MTD.

      - name: rel_diff_current_ytd_vs_previous_ytd
        data_type: numeric
        description: |
          Relative difference between the current year YTD and the previous year YTD.

      - name: target_eom_value
        data_type: numeric
        description: |
          The EOM target value for this metric. This is the value that we aim to 
          achieve by the end of the month. It can be null if the target is not 
          available.

      - name: target_ytd_value
        data_type: numeric
        description: |
          The YTD target value for this metric. This is the cumulative value that we
          aim to achieve by the end of each month with respect to the beginning of the 
          financial year, that will put us to reach the EOFY target. It can be null if
          the target is not available.

      - name: target_eofy_value
        data_type: numeric
        description: |
          The EOFY target value for this metric. This is the value that we aim to 
          achieve by the end of the financial year. It can be null if the target is
          not available.

      - name: diff_current_month_mtd_vs_eom_target
        data_type: numeric
        description: |
          Difference between the current month MTD and the EOM target. It can be null
          if the target is not available.

      - name: diff_current_ytd_vs_ytd_target
        data_type: numeric
        description: |
          Difference between the current year YTD and the YTD target. It can be null
          if the target is not available.

      - name: diff_current_ytd_vs_eofy_target
        data_type: numeric
        description: |
          Difference between the current year YTD and the EOFY target. It can be null
          if the target is not available.

      - name: rel_diff_current_month_mtd_vs_eom_target
        data_type: numeric
        description: |
          Relative difference between the current month MTD and the EOM target. It can be null
          if the target is not available.

      - name: rel_diff_current_ytd_vs_ytd_target
        data_type: numeric
        description: |
          Relative difference between the current year YTD and the YTD target. It can be null
          if the target is not available.

      - name: achievement_rate_current_ytd_vs_eofy_target
        data_type: numeric
        description: |
          Achievement rate between the current year YTD and the EOFY target. It can be null
          if the target is not available.

      - name: rel_diff_with_sign_current_month_mtd_vs_previous_month_eom
        data_type: numeric
        description: |
          Relative difference between the current month MTD and the previous month EOM, 
          with a sign to represent if the relative difference is good (positive) or bad 
          (negative) for our business.

      - name: rel_diff_with_sign_current_month_mtd_vs_previous_year_mtd
        data_type: numeric
        description: |
          Relative difference between the current month MTD and the previous year MTD, 
          with a sign to represent if the relative difference is good (positive) or bad 
          (negative) for our business.

      - name: rel_diff_with_sign_current_ytd_vs_previous_ytd
        data_type: numeric
        description: |
          Relative difference between the current year YTD and the previous year YTD, 
          with a sign to represent if the relative difference is good (positive) or bad 
          (negative) for our business.

      - name: rel_diff_with_sign_current_month_mtd_vs_eom_target
        data_type: numeric
        description: |
          Relative difference between the current month MTD and the EOM target, 
          with a sign to represent if the relative difference is good (positive) or bad 
          (negative) for our business.

      - name: rel_diff_with_sign_current_ytd_vs_ytd_target
        data_type: numeric
        description: |
          Relative difference between the current year YTD and the YTD target, 
          with a sign to represent if the relative difference is good (positive) or bad 
          (negative) for our business.

  - name: mtd_aggregated_metrics_by_deal
    description: |
      This model aggregates the historic information of our business by providing
      different metrics at account level (by id_deal).
      Additionally it provides Deal attributes.
      Metrics displayed in the model range for the past 24 months. Also, churned 
      accounts are available for historical values, until 3 months after the offboarding 
      date.
      Keep in mind that metrics that depend on the invoicing cycle are only available with 
      a time delay. If you need timely information, at your own risk, check the equivalent 
      intermediate model.

    data_tests:
      - dbt_utils.unique_combination_of_columns:
          combination_of_columns:
            - date
            - metric
            - id_deal
    columns:
      - name: year
        data_type: int
        description: Year number of the given date.
        data_tests:
          - not_null

      - name: month
        data_type: int
        description: Month number of the given date.
        data_tests:
          - not_null

      - name: day
        data_type: int
        description: Day monthly number of the given date.
        data_tests:
          - not_null

      - name: is_end_of_month
        data_type: boolean
        description: Is end of month, 1 for yes, 0 for no.
        data_tests:
          - not_null

      - name: is_current_month
        data_type: boolean
        description: |
          Checks if the date is within the current executed month, 
          1 for yes, 0 for no.
        data_tests:
          - not_null

      - name: is_end_of_month_or_yesterday
        data_type: boolean
        description: |
          Checks if the date is end of month or yesterday, 
          1 for yes, 0 for no.
        data_tests:
          - not_null

      - name: first_day_month
        data_type: date
        description: |
          First day of the month corresponding to the date field. 
          It comes from int_dates_mtd logic.
        data_tests:
          - not_null

      - name: date
        data_type: date
        description: |
          Main date for the computation, that is used for filters. 
          It comes from int_dates_mtd logic.
        data_tests:
          - not_null
          - latest_date_is_yesterday

      - name: id_deal
        data_type: string
        description: |
          Unique ID for a deal, or account.
        data_tests:
          - not_null

      - name: deal
        data_type: string
        description: |
          Combination of the ID and the Name of the deal.
        data_tests:
          - not_null

      - name: active_accommodations_per_deal_segmentation
        data_type: string
        description: |
          Segment value based on the number of listings booked in 12 months 
          for a given deal and date.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - "0"
                - "01-05"
                - "06-20"
                - "21-60"
                - "61+"
                - "UNSET"

      - name: main_billing_country_iso_3_per_deal
        data_type: string
        description: |
          ISO 3166-1 alpha-3 main country code in which the Deal is billed.
          In some cases it's null.

      - name: business_scope
        data_type: string
        description: |
          Business scope identifying the metric source.
        data_tests:
          - not_null
          - accepted_values:
              values:
                - "Old Dash"
                - "New Dash"
                - "API"
                - "UNSET"

      - name: account_manager
        data_type: string
        description: |
          Account manager of the deal.
          In some cases it's null.

      - name: deal_lifecycle_state
        data_type: string
        description: |
          Lifecycle state of the deal.

      - name: metric
        data_type: text
        description: Name of the business metric.
        data_tests:
          - not_null

      - name: order_by
        data_type: integer
        description: |
          Order for displaying purposes. Null values are accepted, but keep
          in mind that then there's no default controlled display order.

      - name: number_format
        data_type: text
        description: Allows for grouping and formatting for displaying purposes.
        data_tests:
          - accepted_values:
              values:
                [
                  "integer",
                  "percentage",
                  "currency_gbp",
                  "converted_metric_currency_gbp",
                ]

      - name: value
        data_type: numeric
        description: |
          Numeric value (integer or decimal) that corresponds to the MTD computation of the metric
          at a given date. Note that if the month is not in progress, then this value corresponds
          to the monthly figure.
        data_tests:
          - not_null

      - name: previous_year_value
        data_type: numeric
        description: |
          Numeric value (integer or decimal) that corresponds to the MTD computation of the metric
          on the previous year at a given date.
        data_tests:
          - not_null

      - name: relative_increment
        data_type: numeric
        description: |
          Numeric value that corresponds to the relative increment between value and previous year value,
          following the computation: value / previous_year_value - 1.

      - name: relative_increment_with_sign_format
        data_type: numeric
        description: |
          Relative_increment value multiplied by -1 in case this metric's growth doesn't have a
          positive impact for Truvi, otherwise is equal to relative_increment.
          This value is specially created for formatting in PBI