data-dwh-dbt-project/models/intermediate/cross/schema.yml

models:
  - name: int_daily_currency_exchange_rates
    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 dont' 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).
        tests:
          - not_null
          - unique
      - name: from_currency
        data_type: character
        description: The source currency, represented as an ISO 4217 code.
        tests:
          - not_null
      - name: to_currency
        data_type: character
        description: The target currency, represented as an ISO 4217 code.
        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.
        tests:
          - not_negative_or_zero
          - not_null
      - name: rate_date_utc
        data_type: date
        description: The date in which the rate record is relevant.
        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.
        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.
        tests:
          - not_null
  - name: int_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.
    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.
        tests:
          - not_null
      - name: to_currency
        data_type: character
        description: The source currency, represented as an ISO 4217 code.
        tests:
          - not_null
      - name: rate
        data_type: numeric
        description: The target currency, represented as an ISO 4217 code.
        tests:
          - not_null
      - name: rate_date_utc
        data_type: date
        description: The date in which the rate record is relevant.
        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.
        tests:
          - not_null

  - name: int_mtd_guest_revenue_metrics
    description: |
      This model contains the historic information regarding the guest revenue in an aggregated manner. 
      It's used for the business KPIs. Data is aggregated at the last day of the month and in the
      days necessary for the Month-to-Date computation of the current month.

    columns:
      - name: date
        data_type: date
        description: The date for the month-to-date guest revenue-related metrics.
        tests:
          - not_null
          - unique

  - name: int_monthly_guest_revenue_history_by_deal
    description: |
      This model contains the historic information regarding the guest revenue for each deal id. 
      It's used for the business KPIs in the view by deal id. Data is aggregated at the last
      day of the month, or up to yesterday if it's the current month.
    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 or yesterday for historic guest revenue metrics.
        tests:
          - not_null

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