In the context of Elastic ML, there are really just two, somewhat similar, use cases in which someone would use forecasting. These are as follows:
- Value-focused: Extrapolating a time series into the future to understand a probable future value. This would be akin to answering questions such as: "how many widgets will I sell per day two months from now?"
- Time-focused: Understanding the likely time at which an expected value is to be reached. This would be answering questions similar to: "do I expect to reach 80% utilization in the next week?"
The differences between these two use cases might not just be how the question is asked (how the data is searched), but also how you interpret the output. However, before we delve into a few examples of how to use the forecasting feature, let's take a little time to discuss how it works logistically...
