Understanding the forecasting problem

In Chapter 1, Introduction to ML Engineering, we considered the example of a ML team that has been tasked with providing forecasts of items at the level of individual stores in a retail business. The fictional business users had the following requirements:

• The forecasts should be rendered and accessible via a web-based dashboard.
• The user should be able to request updated forecasts if necessary.
• The forecasts should be carried out at the level of individual stores.
• Users will be interested in their own regions/stores in any one session and not be concerned with global trends.
• The number of requests for updated forecasts in any one session will be small.

Given these requirements, we can work with the business to create the following user stories, which we can put into a tool such as JIRA, as explained in Chapter 2, The Machine Learning Development Process. Some examples of user stories covering these requirements would...