RATIO_TO_REPORT is a powerful #snowflakedb Window function that lets you calculate the ratio of a value to the sum of the values in a window. The following query uses the RATIO_TO_REPORT function to calculate the percentage of the sales by channel (online vs. store) for each day.

Raw Order Data

create or replace table scratch.saqib_ali.TRANSACTIONS (order_id number, amount number, transaction_date date, channel varchar(20));
insert into scratch.saqib_ali.TRANSACTIONS values (1, 10, '2022-12-01', 'store');
insert into scratch.saqib_ali.TRANSACTIONS values (2, 20, '2022-12-01', 'online');
insert into scratch.saqib_ali.TRANSACTIONS values (3, 20, '2022-12-01', 'store');
insert into scratch.saqib_ali.TRANSACTIONS values (4, 20, '2022-12-02', 'store');
insert into scratch.saqib_ali.TRANSACTIONS values (5, 30, '2022-12-02', 'store');
insert into scratch.saqib_ali.TRANSACTIONS values (6, 30, '2022-12-02', ' store');
insert into scratch.saqib_ali.TRANSACTIONS values (7, 20, '2022-12-02', 'store');
select * from scratch.saqib_ali.TRANSACTIONS;
ORDER_ID AMOUNT TRANSACTION_DATE CHANNEL
1 10 2022-12-01 store
2 20 2022-12-01 online
3 20 2022-12-01 store
4 20 2022-12-02 store
5 30 2022-12-02 store
6 30 2022-12-02 store
7 20 2022-12-02 store

SQL Query using the RATIO_TO_REPORT

select
  transaction_date
  , channel
  , sum(amount) as total_sales
  , ratio_to_report(total_sales) over (partition by transaction_date) 
    as channel_percentage
from scratch.saqib_ali.TRANSACTIONS 
group by transaction_date, channel;

Query output

TRANSACTION_DATE CHANNEL TOTAL_SALES CHANNEL_PERCENTAGE
2022-12-01 store 30 0.6
2022-12-01 online 20 0.4
2022-12-02 store 100 1

SQL Query without using the RATIO_TO_REPORT for comparison

select
  transaction_date
  , channel
  , sum(amount) as total_by_channel
  , sum(total_by_channel) over (partition by transaction_date) as total_online_and_store
  , ((total_by_channel / total_online_and_store) * 100)::NUMBER || '%' as channel_percentage
from scratch.saqib_ali.TRANSACTIONS 
group by transaction_date, channel;
TRANSACTION_DATE CHANNEL TOTAL_BY_CHANNEL TOTAL_ONLINE_AND_STORE CHANNEL_PERCENTAGE
2022-12-01 store 30 50 60%
2022-12-01 online 20 50 40%
2022-12-02 store 100 100 100%