cloud-platform/google-cloud/bigquery/bigquery-ml/detect_sales_anomalies/000001_train.sql
create or replace model `sales.hm_sales_anomalies_model`
options(
model_type = 'arima_plus',
time_series_timestamp_col = 'date',
time_series_data_col = 'total_amount_sold',
time_series_id_col = 'item_name',
holiday_region = 'US'
) as (
select
date,
item_description as item_name,
sum(bottles_sold) as total_amount_sold
from
`bigquery-public-data.iowa_liquor_sales.sales`
group by
date,
item_name
having
date between date('2016-01-01') and date('2020-12-31')
and lower(item_name) in (
'black velvet',
'captain morgan spiced rum',
'hawkeye vodka',
"five o'clock vodka",
'fireball cinnamon whiskey'
)
);