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Hello together,
I am currently having a problem regarding the use of "moving averages" to forecast values.
Basically, I have the creation month "cr_month" of tickets and the amount of tickets created per month as a dimension (grey bars). Now, I want to forecast the number of tickets for the next 12 mnths using a linear model, which is working fine via linest_m and linest_b, and the moving average (cf. screenshot).
For the moving average, currently I am using the following logic:
if
(
cr_month < 202201
, count(distinct Ticket_ID)
, RangeAvg(Above(count(distinct Ticket_ID),0,12))
)
So my question is: How do I estimate /forecast the number of tickets for the months 202202 - 202301? Unfortunately, the moving average curve is currently decreasing.
Thank you very much!
Best regards
Tina
1. moving average and forecasting are two fully seperate things!
as you already solved the linear variant. have a look at the other statistical forecast variants (exp, log).
Logarithmic ($1 iy your measure (count) and $2 is your date-field):
linest_m(total aggr(If($2<=today(),$1),$2),(Aggr(Log(Rowno()) * $2, $2)))
* (Aggr(Log(Rowno()) * $2, $2))+ linest_b(total aggr(If($2<=today(),$1),$2),
(Aggr(Log(Rowno()) * $2, $2)));
exponential ($1 iy your measure (count) and $2 is your date-field):
exp(linest_b(total log(aggr(If($2<=today(),$1),$2)),$2))
* POW( e(), linest_m(total log(aggr(If($2<=today(),$1),$2)),$2) * $2);
If you want a more detailied actual forecasting or as you mentioned areal "estimating" you have to add advanced analytic connections to use machine learning models.
Thank you!