Forecasting theory of operation
The first thing to realize is that the act of invoking a forecast on data is that it is an extension of an existing Anomaly Detection job. In other words, you need to have an Anomaly Detection job configured, and that job needs to have analyzed historical data before you can forecast on that data. This is because the forecasting process uses the models that are created by the Anomaly Detection job. To forecast the data, you need to follow the same steps that were used to create an Anomaly Detection job as described in other chapters. If anomalies were generated by the execution of that job, you can disregard them if your only purpose is to execute forecasting. Once the job has learned on some historical data, the model or models (if the job is configured to analyze data from more than one time series) associated with that job are current and up to date, as represented in the following diagram: