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I am looking to generate and compare forecasts using the ETS and the ARIMA models where my dataset is at a slightly disaggregated level. This means that my data set would have duplicate date entries. Please see example below:
I would like to generate a forecast for 1A, 1B, 2A, 2B and 3B. I noticed that Alteryx gave me an error when I had my data set up this way. Can you help me with the methodology I can employ to generate a forecast at this level?
Hi there - this is very helpful. However, with the real dataset I might end up having close to 2,000 Attribute 1 and Attribute 2 combinations which might make it difficult to incorporate into the flow. Is there any way to "group" attribute 1 and 2 prior to generating the forecast?