First step on refactor of kpis:
- Remove relative incremental vs. previous year computation from the source model (`mtd_booking_metrics`, in this case)
- Aggregate the source mtd global metrics models into a single model: `int_mtd_vs_previous_year_metrics` (to enable multi-source weighted metric computation) and compute previous year value and relative increment. Now this logic is encapsulated into a macro `calculate_safe_relative_increment`, easing readability and providing a bit more robustness.
- End-to-end continuity to not break the existing dashboard display in `int_core__mtd_aggregated_metrics`
This is a substep of the global change. All info can be found in the documentation [here](https://www.notion.so/knowyourguest-superhog/Refactoring-Business-KPIs-5deb6aadddb34884ae90339402ac16e3)
Related work items: #18202
IMPORTANT: this PR was merged and reverted. The division by 0 error has been fixed in the last commit
Adds the following metrics:
- Guest Revenue
by both visions (global and by deal id)
It creates 2 new models:
- int_mtd_guest_revenue_metrics
- int_monthly_guest_revenue_history_by_deal
the approaches are similar in the sense that we retrieve the information from the int_core__verification_payments and a filter by a PAID status. I checked and the aggregated volumes of the figures correspond to the decimal as what is reported to the guest_payments dashboard (aggregating the information from the currency tab)
Same as last PR, this one does not exposes the data since a refactor of how the code is structured will follow shortly.
Related work items: #18107
Adds the following metrics:
- Guest Revenue
by both visions (global and by deal id)
It creates 2 new models:
- int_core__mtd_guest_revenue_metrics
- int_core__monthly_guest_revenue_history_by_deal
the approaches are similar in the sense that we retrieve the information from the int_core__verification_payments and a filter by a PAID status. I checked and the aggregated volumes of the figures correspond to the decimal as what is reported to the guest_payments dashboard (aggregating the information from the currency tab)
Same as last PR, this one does not exposes the data since a refactor of how the code is structured will follow shortly.
Reverts !2199
Related work items: #18107
Adds the following metrics:
- Guest Revenue
by both visions (global and by deal id)
It creates 2 new models:
- int_core__mtd_guest_revenue_metrics
- int_core__monthly_guest_revenue_history_by_deal
the approaches are similar in the sense that we retrieve the information from the int_core__verification_payments and a filter by a PAID status. I checked and the aggregated volumes of the figures correspond to the decimal as what is reported to the guest_payments dashboard (aggregating the information from the currency tab)
Same as last PR, this one does not exposes the data since a refactor of how the code is structured will follow shortly.
Related work items: #18107
This is a first approach to compute some easy metrics for the "deal" based business kpis. At this stage, it contains the information of bookings (created, checkout, cancelled) per deal and month, including both historic months as well as the current one. This do not contain MTD computation because it's overkill to do a MTD at deal level (+ we have 1k deals, so scalability can become a problem in the future)
Models:
- **int_dates_by_deal**: simple model that reads from **int_dates** and just joins it with **unified_users** to retrieve the deals. It will be used as the 'source of truth' for which deals should be considered in a given month, basically, since the first host associated to a deal is created (not necessarily booked)
- **int_core__monthly_booking_history_by_deal**: it contains the history of bookings per deal id in a monthly basis. It should be easy enough to integrate here, in the future and if needed, B2B macro segmentation.
In terms of performance, comparing the model **int_core__monthly_booking_history_by_deal** and **int_core__mtd_booking_metrics** you'll see that I removed the joined with the **int_dates_xxx** in the CTEs. This is because I want to avoid a double join of date & deal that I tried and I stopped after 5 min running. Since this computation is in a monthly basis - no MTD - it's easy enough to just apply the **int_dates_by_deal** on the last part of the query. With this approach, it runs in 7 seconds.
Related work items: #17689
As today it's 1st of July, the logic of selecting all days of the current month for MTD purposes on the business KPIs is ko, since we select up to yesterday.
This PR allows to consider the last day of the previous month as 'current month' only for the first day of the following month, thus ensuring that the most up-to-date data is always displayed in the MTD tab.
Related work items: #17745
