In a dataset, measures are typically numerical values that we want to analyze. Given that the task is to analyze the average revenue per product in different regions over time, the fields that qualify as measures are 'Revenue' and 'Quantity'. Measures are quantitative data, and in this case, 'Revenue' (a decimal number) represents the income from sales, while 'Quantity' (a whole number) represents the number of units sold. These are the appropriate fields to conduct numerical analysis and calculations, such as finding averages. On the other hand, 'Order Date', 'Customer Region', and 'Product Name' are categorical data types and are generally used as dimensions to categorize and group the data rather than perform arithmetic operations.