- How Many Forecasts can be Requested in SAP Analytics Cloud Smart Predict?
- Error : Training ended with errors. For more details, open the Status Panel." while training a forecast model in Smart Predict
- Model Status : "No forecast is available as there aren't enough future values for infulencers to cover all of the requested forecast dates. Try one of the following solutions - Reduce the number of requested forecastes. - Use another data source with values for the full requested forecast period. - If you have access to the data source, add values for infulencers over the full requested forecast period.:
- Error "no forecast is available" while training a forecast model in Smart Predict in SAP Analytics Cloud
- Error: "Predictive forecast requires more data points"
- SAP Analytics Cloud (SAC)
- Smart Predict
Reproducing the Issue
- Logon to SAC.
- Create -> Predictive Scenario -> Forecast.
- The detailed description could be found in SAC Guide.
- For the forecast model which contains influencers, the forecast value can be set to less than or equal to the number of future values in datasource containing influencer value.
For the forecast model which doesn't contain influencers - only "Date" and "Signal", the forecase number can be set to 1/5 of the datasource. If the datasource value is less than or equal to 12, then 1 only can be predicted.
- 2420312 - "Error: Predictive forecast requires more data points" when trying to run a Predictive forecast in BusinessObjects Cloud.
- SAP Analytics Cloud Predictive Planning – Frequently Asked Questions
Question: when writing back the predictive forecasts to the private version, I received an error that not all forecasts could be written back and that the planning model time range should be extended. I am not sure why I receive this error and what to do. Can you please help?
Answer: irregular time series might cause the predictive forecasts to extend beyond what the end-user expects as a range. If I have only one data point filled every two years, Predictive Planning will reproduce this similar pattern in the future. The typical way to prevent this message from appearing is to exclude the entities causing this problem up-front or fixing the fact that data is too sparse. Such issues can be spotted via a dedicated SAC story to pre-analyze the data or using the “Row Count” per entity once the Smart Predict model has been trained.
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