Du kan skapa en enkel prognos med hjälp av REGR linjära regressionsfunktioner.
--Ordinary least squares forecast for each customer for the next year.
select
cust_id,
max(year) +1 forecast_year,
-- y = mx+b
regr_slope(revenue, year)
* (max(year) + 1)
+ regr_intercept(revenue, year) forecasted_revenue
from customer_data
group by cust_id;
CUST_ID FORECAST_YEAR FORECASTED_REVENUE
------- ------------- ------------------
1 2018 730868
2 2018 50148
4 2018 7483
3 2018 -9920
Nedan är exempelschemat. Eller så kan du använda denna SQLFiddle .
create table customer_data
(
cust_id number,
year number,
revenue number
);
insert into customer_data
select 1, 2016, 679862 from dual union all
select 1, 2017, 705365 from dual union all
select 2, 2016, 51074 from dual union all
select 2, 2017, 50611 from dual union all
select 3, 2016, 190706 from dual union all
select 3, 2017, 90393 from dual union all
select 4, 2016, 31649 from dual union all
select 4, 2017, 19566 from dual;
REGR
funktion handlar om nummerpar, den förstår inte affärsregler som "intäkter kan inte vara under 0". Om du vill begränsa prognoserna till att alltid ligga på eller över 0, ett CASE
uttryck kan hjälpa:
--Forecasted revenue, with minimum forecast of 0.
select cust_id, forecast_year,
case when forecasted_revenue < 0 then 0 else forecasted_revenue end forecasted_revenue
from
(
--Ordinary least squares forecast for each customer for the next year.
select
cust_id,
max(year) +1 forecast_year,
-- y = mx+b
regr_slope(revenue, year)
* (max(year) + 1)
+ regr_intercept(revenue, year) forecasted_revenue
from customer_data
group by cust_id
);
CUST_ID FORECAST_YEAR FORECASTED_REVENUE
------- ------------- ------------------
1 2018 730868
2 2018 50148
4 2018 7483
3 2018 0