# Description
Eliminates models that have been switched with new kpis flow.
Also deletes temporary tests and schema entries.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [NA] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [X] I have checked for DRY opportunities with other models and docs.
- [NA] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23762
# Description
Adds listing metrics model. It's a bit similar as the Deal metrics, but here we can aggregate by deal :)
I'm aware that int_kpis__metric_daily_listings takes quite a bit (3 min). To be optimised later on.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23567
# Description
Cleans Xero models for the old KPIs flow, temporary tests and schema entries
# Checklist
- [X] The edited models and dependants run properly with production data.
- [NA] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [NA] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23760
# Description
Changes:
* Creates lifecycle_daily_deal, metric_daily_deals and agg_daily_deals. These follow a different strategy due to the nature of the metrics
* Modifies the dimension macro to ensure deal dimension is included in all models except these ones
* Fixes production issue on currently deployed deal lifecycle and metrics
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23566
# Description
Same old story: includes all metrics coming from Xero.
Adds a daily model, monthly, mtd + monthly agg and mtd agg
A test to compare values new vs. old
AND fixes the issue I mentioned with the timestamp - an issue in the old KPIs.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23565
# Description
Removes old computation of KPIs of Bookings, Guest Journeys and Guest Payments, after yesterday's switch to new computation.
It cleans 1) models 2) schema entries and 3) temporary tests.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [NA] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them. **(Except for the duplicated Booking to Product Bundle)**
- [X] I have checked for DRY opportunities with other models and docs.
- [NA] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Remove previous KPIs computation for Bookings, Guest Journeys and Guest Payments
Related work items: #23576
# Description
Adds 2 new metrics:
- xero_host_resolution_amount_paid_in_gbp
- xero_host_resolution_payment_count
Effectively it will split the "real" invoicing sources of revenue from "host resolution payments". This was already reading from 2 different Xero models (bank transactions vs. sales).
We have as usual:
- 1 Daily metric model
- 2 MTD/Monthly metric model
- 2 MTD/Monthly agg model (I already changed the name to agg instead of aggregated)
- 1 test to compare the values match the current setup
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23565
# Description
Adds Check-Out, Cancelled and Billable Bookings in the new KPI flow.
For each of these metrics, it includes:
* Daily model
* Monthly/MTD without dimension aggregates
* Monthly/MTD with dimension aggregates
* Schema entries for the abovementioned 5 models
* Temporary test to compare the different metrics against current production KPIs
I also implemented a quick performance fix that removes the dependency of Billable Bookings from Booking Charge Events, since Bookings table already contains the needed information.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23454
# Description
Adds Guest Payments metrics, namely:
* deposit_fees_in_gbp
* waiver_payments_in_gbp
* checkin_cover_fees_in_gbp
* total_guest_payments_in_gbp
It includes:
* Daily model
* Monthly/MTD without dimension aggregates
* Monthly/MTD with dimension aggregates
* Schema entries for the abovementioned 5 models
* Temporary test to compare the different metrics against current production KPIs
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23453
# Description
Adds GJ with Payment. It includes:
* Daily model
* Monthly/MTD without dimension aggregates
* Monthly/MTD with dimension aggregates
* Schema entries for the abovementioned 5 models
* Temporary test to compare against current production KPIs
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23453
# Description
Adds GJ Created, Started and Completed.
Each model has:
* A Daily model
* A Monthly/MTD without dimension aggregate
* A Monthly/MTD with dimension aggregate
* A comparison vs. the current flow of KPIs in the form of a test
It's quite similar as for Created Bookings. The main difference is that 1) reads from Verification Requests table and 2) I don't compute a New Dash dimension. This helps actually validating the logic of the dimension configuration macro, which works good.
I confirm that the 3 tests of comparison vs. current data work well in my local - i.e. identical content for Global, Billing Country for these 3 metrics since 2022.
This does not include:
* Guest Journeys with Payment. I'll do this in a separated PR
* Guest Payments/Revenue. I'll do this in a separated PR
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs. **Briefly discussed with Pablo, we'll leave it like this for the time being**
- [X] I've picked the right materialization for the affected models. **Runs quite fast**
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #23453
# Description
Creates skeleton for new KPIs data flow for created_bookings metric. Details are accessible [here](https://www.notion.so/knowyourguest-superhog/KPIs-Refactor-Let-s-go-daily-2024-10-23-1280446ff9c980dc87a3dc7453e95f06?pvs=4#12a0446ff9c98085bf4dfc77f6fc22f7)
In essence:
* Models are created in intermediate in a kpis folder.
* Models have a daily segmentation. This includes `created_bookings` models, but also the daily lifecycle per listing and the segmentation. It also adds a `dimension_dates` model specific for KPIs. These have all the dimensions already in place and handle all the crazy logic.
* Other time aggregation models simply read from existing daily models which are much easier (`int_kpis__metric_mtd_created_bookings` and `int_kpis__metric_monthly_created_bookings`).
* Dimensionality aggregation can be easily added within a given timeframe (daily, mtd, monthly). For instance, I do it for mtd in the `int_kpis__aggregated_mtd_created_bookings` and for monthly in `int_kpis__aggregated_monthly_created_bookings`
* Macro configuration for dimensions: Allows to set any specific dimension for `aggregated` models. By default, the subset of global, by billing country, by number of listings and by deal apply - since these are needed for Main KPIs. I added an example with Dash Source, that currently does not exist and it's currently configured as only appearing for created bookings.
* Testing `aggregated` models completeness. A new macro called `assert_dimension_completeness` is available that ensures additive metrics are consistent vs. the global result, configurable at schema level.
* Testing refactor impact. I'm aware that changing the lifecycle model to daily impacts the volumes for listing segments. For the rest, I added a `tmp` test that checks that the dimension and dimension value per date exactly match comparing new vs. old computation.
Latest edits:
* Changed naming convention
* Split of MTD and Monthly. Now these are 2 different entities, as stated in `int_kpis__dimension_dates`.
* Added start_date and end_date for models that contemplate a range (mtd, monthly).
* Added a small readme entry in the kpis folders. Mostly it states nomenclature and some first conventions.
Dbt docs:
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs. **Likely we'll be able to add macros for mtd and dim_agg models. We will see later on.**
- [ ] I've picked the right materialization for the affected models. **Models run ok except for the daily lifecycle of listings, which lasts several minutes in the first run. Model curr...
# Description
Exposes Churn Rates into Main KPIs, specifically Revenue Churn Rate, Bookings Churn Rate and Listings Churn Rate. This is based on the average approach.
Additionally, it adds these 3 metrics in the kpis_additive_metrics_per_dimension_are_consistent test.
Additionally, it removes from int_mtd_vs_previous_year_metrics the computation of the additive Churn Rates. The removal of further unused code will be handled in a separated PR.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [NA] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #22691
# Description
Adapts revenue figures in Main KPIs - MTD scope or global view. This includes MTD, Monthly Overview, Global Evolution over Time, Detail by Category. In essence, everything that is not by deal.
The changes are mainly 2:
* Remove the line that deducts the `Waiver Amount Paid Back to Hosts` in all metrics except the `Waiver Net Fees`. This effectively means that the previous `Guest Revenue` = `Guest Payments`, thus I dropped all 3 `Guest Payments` metrics.
* Do a renaming at metric display level, but not in the code. This means that I remove the computation of `guest_revenue_in_gbp` for instance and keep `guest_payments_in_gbp`, and apply the renaming later on, since the modelisation already accounts for defining metric names differently from those of the fields. For the rest of metrics, I revised all metrics name and did changes based on the [whiteboard](https://whiteboard.office.com/me/whiteboards/p/c3BvOmh0dHBzOi8vZ3VhcmRob2ctbXkuc2hhcmVwb2ludC5jb20vcGVyc29uYWwvcGFibG9fbWFydGluX3N1cGVyaG9nX2NvbQ%3d%3d/b!T2D3opQuBECSDnhuFZrUacFu3TxvSvdIsnI4Dxsh2IuaB1AigbciRqkqte61I4wz/01H5SI4J4L7HTPJGUT7JGYKTOSQYYWACXU). I also changed the dedicated data tests in Main KPIs to ensure it's working. I also changed the exclusion logic in reporting based on the name of the metric to not display metrics that depend on the invoicing cycle unless it's 2 months ago or before.
To keep in mind:
* Merging this will automatically display the new figures/naming in production. Might be wise to communicate to stakeholders since some key metrics (namely, Guest Revenue / Total Revenue) will change the meaning.
* We also need to do these changes in the metrics by deal part of the computation. I'd do first the removal of these fields in the PBI report (and take the opportunity to change the Data Catalogue) and then do the PR in DWH to change the logic. Before that though let's check that the names included in this PR are the correct ones :)
# Checklist
- [X] The edited models and dependants run properly with production data.
- [NA] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [NA] I have checked for DRY opportunities with other models and docs.
- [NA] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #22688
# Description
This PR adapts the outlier detection test for KPIs. Specifically:
1) It removes not additive lifecycle metrics, which are:
- Churning Listings/Deals
- Listings/Deals Booked in Month/6 Months/12 Months
this is because the test computes data at daily level by just doing value/number of days. The thing is that for all these metrics, Listing/Deal bookings are computed **uniquely over a month**, i.e., if a listing is booked 100 times in a single month, it will only appear as once. Thus it makes it fail on early days of the month. Similar case for Churn, in this case, at the beginning of the month we have the total maximum number of listing/deals that are expected to churn if nothing happens, and this can decrease a bit over time if these get reactivated.
2) I reduced the variance threshold from 10 to 8, meaning now the alerts will raise more often. This is because we're removing some wrongly assessed metrics from the computation, thus I feel we can leave with better fine-grained detection. It could be even further reduced (8 is still super high tolerance) since today maximum signal-to-noise ratio was less than 4 on checkout bookings, but I'd propose to see how it goes in the following days and then assess if it's necessary to reduce it even further.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [ ] The edited models are sufficiently documented.
- [ ] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
# Description
Adds 2 tests for KPIs to:
1. Check that the values observed in the last run for the dimensions other than Global are consistent for additive metrics. Consistent does not mean exact, though
2. Check that the values observed in the last run for Global dimension are similar to what was observed previously, to raise an alert in case of outliers. This one is tricky because there's possibilities to have false positives, so extensive documentation on the test and parameters has been provided.
Note: This runs well targeting production. It also detects the cancelled bookings issue if it was supposed to run on 31st of August. Once an alert is raised, since it only takes into account the last update, usually will not raise it in the next day.
# Checklist (does not apply)
- [ ] The edited models and dependants run properly with production data.
- [ ] The edited models are sufficiently documented.
- [ ] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Adding specific business tests for kpis
Related work items: #20824
