As a data scientist for a multinational beverage company, you are tasked with developing a machine learning model to predict the profitability of a new line of natural flavored bottled waters across different regions. The historical data available includes product categories, sales, expenses, and profits for all regions. The model needs to consider geographical variations in consumer preferences and operational costs. Given the constraints of ensuring the model is scalable across regions and compliant with data privacy regulations, which of the following input and output configurations would best suit your model? Choose the best option.