Use dynamic years instead of fixed years on models used for NTD Validation

[erikamov]

Description

Use dynamic years (this_year and last_year) instead of fixed years on models used for NTD Validation. I am using the same logic from fct_ntd_rr20_service_checks.sql that was already created using those dynamic years. So the variable this_year is based on the date that the DAG run started and the last_year is just a previous year.

I also turn int_ntd_rr20_service_1alldata into a materialize view as requested by previous Github Warehouse report.

This change also make the models ready for use on next years without having to change it again.

Type of change

• [ ] Bug fix (non-breaking change which fixes an issue)
• [x] New feature
• [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
• [ ] Documentation

How has this been tested?

Tested creating all models running locally:

poetry run dbt run --select "models/staging/ntd_validation/"
poetry run dbt run --select "models/intermediate/ntd_validation/"
poetry run dbt run --select "models/mart/ntd_validation/"

Those models were successfully created on cal-itp-data-infra-staging.erika_staging and cal-itp-data-infra-staging.erika_mart_ntd_validation and can be validated there.

Post-merge follow-ups

• [ ] No action required
• [x] Actions required (specified below)

Once the next transform_warehouse runs we can validate the changes on those models in cal-itp-data-infra.

[github-actions[bot]]

Warehouse report 📦

DAG

Legend (in order of precedence)

Resource type	Indicator	Resolution
Large table-materialized model	Orange	Make the model incremental
Large model without partitioning or clustering	Orange	Add partitioning and/or clustering
View with more than one child	Yellow	Materialize as a table or incremental
Incremental	Light green
Table	Green
View	White

[erikamov]

@KatrinaMKaiser This PR is ready for review. Let me know if you and Christian decided to wait for his return on Monday or if we can merge it today.