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A Salesforce AI Specialist wants to create a predictive model using Model Builder. What is the first step they should take?

  1. Input expected sales revenue figures directly

  2. Select "Create a model from scratch" and choose historical sales data as the source

  3. Increase dataset rows to exceed 20 million

  4. Analyze model outputs against actual sales data

The correct answer is: Select "Create a model from scratch" and choose historical sales data as the source

To create a predictive model using Model Builder in Salesforce, the initial step involves selecting "Create a model from scratch" and choosing historical sales data as the source. This is crucial because the model relies on historical data to learn patterns, trends, and relationships that can be used for making predictions. Historical data serves as the foundation for training the predictive model, allowing it to understand the variables and their influence on sales outcomes. Beginning with this selection allows the specialist to define the parameters and data elements that will be critical in building a robust model. It sets the stage for subsequent steps, such as data preparation and refinement, as well as adding any necessary features for improved accuracy. Choosing to input expected sales revenue figures directly, increasing dataset rows, or analyzing model outputs are actions that may occur later in the modeling process but are not the foundational first step necessary for setting up the predictive analysis effectively.