Snowflake your team can trust, and afford.

-- bi/dau.sql (before)
-- 6 minutes end to end. Scans 1.4B events on raw.events.
-- One XL warehouse, growing every month.
-- Run from a Looker Studio data source by an analyst.
select
  user_id,
  date(event_at) as day
from raw.events
where event_at > current_date - 30
group by 1, 2

-- models/marts/fct_dau.sql (after)
{{ config(
  materialized='incremental',
  incremental_strategy='merge',
  unique_key=['user_id', 'day'],
  cluster_by=['user_id', 'day'],
  snowflake_warehouse='transforming_xs',
  on_schema_change='append_new_columns',
  tags=['product']
) }}

with events as (select * from {{ ref('stg_events') }})
select
  user_id::number as user_id,
  date(event_at)  as day,
  count(*)        as events
from events
{% if is_incremental() %}
  where event_at > (select max(day) from {{ this }})
{% endif %}
group by 1, 2