Divide columns after Group By call

Question

Coming from an R/Dplyr background, I've written the following code in R:

staff_time2 <- staff_time %>% 
  mutate(Dashboard_Group = "CC", Occupied_Time = HandleTime + AvailableTime) %>% 
  select(Date, Dashboard_Group, HandleTime, Occupied_Time, WorkingTime, LoginTime) %>% 
  mutate(Date = stringi::stri_sub(Date,1, -9), Date = mdy(Date)) %>% 
  filter(Date >= "2020-08-16" & Date <= "2020-08-22") %>% 
  group_by(Dashboard_Group) %>% 
  mutate(BusyTime = sum(HandleTime), OccupiedTime = sum(Occupied_Time), 
         WorkTime = sum(WorkingTime), Login = sum(LoginTime)) %>% 
  ungroup() %>% 
  mutate(Occupancy = BusyTime/OccupiedTime, Utilization = WorkTime/Login ) 

Now I am trying to do the same thing in SQL on Google Big Query. I've accomplished it with two separate queries:

Query 1:

SELECT  
'Contact Center' AS Dashboard_Group, 
sum((HandleTime + AvailableTime)) AS Occupied_Time,
sum(WorkingTime) AS Working_Time, 
sum(LoginTime) AS Login,
sum(HandleTime) AS BusyTime,
FROM `DATABASE.tblStaffTime`
WHERE Date BETWEEN "2020-08-16" AND "2020-08-22"
GROUP BY Dashboard_Group;

Query 2:

SELECT 
(BusyTime/Occupied_Time) AS Occupancy,
(Working_Time/Login) AS Utilization,
FROM `DATABASE.occupancy_and_utilization_1`;

Query 2 simply takes the results from Query 1 and divides two of the columns. Here are the results from Query 1:

I just want to divide BusyTime by Occupied_Time and Working_Time by Login . How can I combine these into one query?

Answer 1

I just want to divide BusyTime by Occupied_Time and Working_Time by Login .

You can repeat the sum() s (or use a subquery or CTE). Consider:

SELECT  
    'Contact Center' AS Dashboard_Group, 
    sum(HandleTime + AvailableTime) AS Occupied_Time,
    sum(WorkingTime) AS Working_Time, 
    sum(LoginTime) AS Login,
    sum(HandleTime) AS BusyTime,
    sum(HandleTime) / sum(HandleTime + AvailableTime) as Occupancy,
    sum(WorkingTime) / sum(LoginTime) as Utilization
FROM `DATABASE.tblStaffTime`
WHERE Date BETWEEN '2020-08-16' AND '2020-08-22'
GROUP BY Dashboard_Group;