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Forecast time series function in OBIEE 12c
Hi,
I have a forecast function with below formula
FORECAST("Sales", ("Year" timeYear, "Qtr" timeQuarter),'forecast','modelType=arima;numPeriods=%1;predictionInterval=70;', 3)
And for the highlighted fields above instead of using static values I would like to use a column in place of it. Ex: Product Expiry in periods.
So that in my analysis I would be using Year, Quarter, Product,Sales, Forecast Sales and to show how many periods the forecast needs to show it should be based on product expiry period column.
If I am trying to use this column directly in the above formula its erroring out. Its working with presentation variable but I should not use presentation variable.
Any other ideas please.
Thanks
Answers
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Can you post the exact error that manifests when you feed in your table based values?
The more information you give the doctor the more likely you will get an accurate diagnosis....
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Thanks for the reply.
Below is the error I am getting if I use a column instead of static number.
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"if I use a column instead of a static number" - presuming that all other things are equal then have you also checked that your column will always have values of the range and type that the function can handle for that parameter?
Is your value a double where the function needs real integers?
i.e. could the column contain nulls, negatives or fractions that the function cannot cope with?
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First, have you try it with a INTEGER DATATYPE in you RPD? do a little proof of concept with just one row and data that could be consistent.
Regards,
Cesar
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Isn't that effectively what I just said?
"have you also checked that your column will always have values of the range and type that the function can handle for that parameter"
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The column Product Expiry in periods is of double data type. I have tried changing it into integer and tried and still getting the same error.
I am filtering for one product and trying to see the results. So for that product it will not have any null or negative numbers.
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Hi,
Can you try filtering your result set down, such that you only get values where ... cast (your value as int) is equal to is in 1,2,3 - where 1,2,3 are values that definitely yield a good result when you put the value explicitly rather than via the measure
If this does not return the error then your problem is down to the range of values.
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