You are tasked with predicting a customer's likelihood of purchasing your company's products using a linear regression model on BigQuery ML. The dataset includes categorical variables such as city names, which need to be transformed into a numerical format suitable for the model. The solution must minimize coding effort, preserve all relevant variables, and ensure the model's performance is not adversely affected by the transformation. Given these constraints, which of the following methods is the most efficient and effective for structuring the data? Choose the best option.