Oracle 21c

By using db<>fiddle, you agree to license everything you submit by Creative Commons CC0.

create table New_customer_data
(
	Cust_ID number,
    State varchar(100),
    City varchar(100),	
	year number,
    id_month number,
	revenue number
);
insert into New_customer_data
select 1, 'MN' , 'Minneapolis', 2016, 1, 679862 from dual union all
select 1, 'IL', 'Chicago' , 2016,  2, 11862 from dual union all
select 1,  'MN' , 'Minneapolis', 2017,  1,547365 from dual union all
select 1, 'IL', 'Chicago' , 2017,  2, 705365 from dual union all
select 2, 'CA', 'San Diego',  2016, 1,  51074  from dual union all
select 2, 'CA', 'LA', 2016, 2, 598862 from dual union all
select 2, 'CA', 'San Diego',  2017,  1, 705365 from dual union all
select 2,'CA', 'LA',  2017,  2, 50611  from dual union all
select 3, 'CA', 'Santa Monica', 2016,  1, 190706 from dual union all
select 3, 'IL', 'Evanston', 2016, 2, 679862 from dual union all
select 3, 'CA', 'Santa Monica', 2017,  1, 705365 from dual union all
select 3, 'IL', 'Evanston', 2017, 2,  90393  from dual union all
select 4, 'MN', 'Shakopee',  2016, 1,  31649  from dual union all
select 4, 'FL', 'Miami', 2016, 2,888862 from dual union all
select 4, 'MN', 'Shakopee', 2017,  1, 125365 from dual union all
select 4, 'FL', 'Miami',  2017, 2,  30566  from dual;
16 rows affected

select cust_id,
       city,
       state,
       id_month,
       max(year) +1 forecast_year,
       regr_slope(revenue, year)
         * (max(year) + 1)
         + regr_intercept(revenue, year) forecasted_revenue
from   New_customer_data c 
group by
       Cust_ID,
       city,
       state,
       id_month;


CUST_ID
CITY
STATE
ID_MONTH
FORECAST_YEAR
FORECASTED_REVENUE


1
Minneapolis
MN
1
2018
414868

1
Chicago
IL
2
2018
1398868

2
San Diego
CA
1
2018
1359656

2
LA
CA
2
2018
-497640

3
Santa Monica
CA
1
2018
1220024

3
Evanston
IL
2
2018
-499076

4
Shakopee
MN
1
2018
219081

4
Miami
FL
2
2018
-827730

CUST_ID	CITY	STATE	ID_MONTH	FORECAST_YEAR	FORECASTED_REVENUE
1	Minneapolis	MN	1	2018	414868
1	Chicago	IL	2	2018	1398868
2	San Diego	CA	1	2018	1359656
2	LA	CA	2	2018	-497640
3	Santa Monica	CA	1	2018	1220024
3	Evanston	IL	2	2018	-499076
4	Shakopee	MN	1	2018	219081
4	Miami	FL	2	2018	-827730