What is the first step a Salesforce AI Specialist should take when using Model Builder for a predictive model?

The initial step for a Salesforce AI Specialist when using Model Builder for a predictive model is to select "Create a model from scratch" and identify the historical sales data as the source. This foundational action is crucial because it establishes the basis for the model's learning process. Historical sales data provides the relevant information and context that the model will analyze to discern patterns and relationships, ultimately allowing it to predict future sales outcomes accurately.

Starting with the creation of a model and selecting a valid data source is essential in predictive modeling because it ensures that the model is training on appropriate and relevant information that reflects past performance. This systematic approach lays the groundwork for the model’s effectiveness, as the more relevant and comprehensive the data, the better the predictions will be.

Other approaches, such as increasing the number of rows or directly inputting expected figures, may not address the need for a well-defined starting point that includes historical insights. Similarly, running simulations without establishing a model based on historical data would not yield useful insights, as the simulations would lack the necessary analytical foundation.