Free · Open Source · MIT

NZ + Australia
in one date dimension.

One combined calendar table for Power BI, SQL and dbt — both countries, 2015–2050, with a single Country column, per-country fiscal years and every regional holiday flag from both date dimensions, side by side.

2015–2050 · 26,298 rows · both countries · no signup, no email wall.

Also available: New Zealand · Australia

One table for trans-Tasman reporting,
instead of two calendars you have to reconcile yourself.

One Country column

Every row is tagged NZ or AU — filter, join or slice by country without maintaining two separate calendar tables side by side.

Per-country fiscal years

New Zealand's 1 April – 31 March and Australia's 1 July – 30 June, each calculated correctly for its own rows — no averaging, no compromise convention.

Country-prefixed regional flags

IsHoliday_NZ_<region> and IsHoliday_AU_<STATE> columns sit side by side, so NZ's 17 provincial anniversaries and AU's 8 states/territories are both addressable without column-name collisions.

Both countries' public holidays

National holidays for New Zealand and Australia in the same table — including Matariki and Mondayisation for NZ, and state-specific days like Melbourne Cup for AU.

Actually maintained

Holiday logic comes from the actively-maintained python-holidays library — not a hand-rolled table that goes stale the moment either country's calendar changes.

Free & open

MIT-licensed code, CC BY 4.0 data. Use it, fork it, ship it — commercially too.

Five formats, ready now. The Power BI template's next.

CSV available T-SQL available Snowflake available Databricks available Power Query (M) available Power BI template soon

All generated from the same source of truth as the single-country tables, so every format is guaranteed identical. CSV, T-SQL, Snowflake, Databricks and Power Query (M) are ready to grab for the combined table now. Need dbt? The combined table doesn't ship its own dbt package — grab the NZ or AU dbt models instead. Watch the repo for the Power BI template.

Loaded into your model in about a minute.

1

Download

Grab the CSV above, or clone the repo if you want to generate a custom date range.

2

Load it

Import the CSV into Power BI, or load it into your warehouse as your combined dim_date table — filter on Country per report page or model.

3

Mark & go

In Power BI, mark it as a date table on the Date column and your time-intelligence just works for both countries at once.

Want this wired into reporting that actually answers your questions?

A date table is the easy part. We build the dashboards, data platforms and automation that turn your numbers into decisions. That's literally what we do.

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