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PROFESSIONAL-DATA-ENGINEER · Question #243
You are working on a linear regression model on BigQuery ML to predict a customer's likelihood of purchasing your company's products. Your model uses a city name variable as a key predictive component
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Submitted by valeria.br· Mar 30, 2026Building and operationalizing data processing systems
Question
You are working on a linear regression model on BigQuery ML to predict a customer's likelihood of purchasing your company's products. Your model uses a city name variable as a key predictive component. In order to train and serve the model, your data must be organized in columns. You want to prepare your data using the least amount of coding while maintaining the predictable variables. What should you do?
Options
- ACreate a new view with BigQuery that does not include a column with city information.
- BUse SQL in BigQuery to transform the state column using a one-hot encoding method, and make each city a column with binary values.
- CUse TensorFlow to create a categorical variable with a vocabulary list.
- DUse Cloud Data Fusion to assign each city to a region that is labeled as 1, 2, 3, 4, or 5, and then use that number to represent the city in the model.
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Topics
#Cloud Data Fusion#Feature Engineering#Categorical Data#BigQuery ML