GCP Professional Data Engineer Practice Question

Define the preprocessing inside the TRANSFORM clause of the CREATE MODEL statement. By calling ML.IMPUTER on usage_minutes and tenure_days you ensure mean imputation for missing numeric values, and applying ML.ONE_HOT_ENCODER to plan_type converts the high-cardinality string column into sparse indicator features, optionally limited by top_k. BigQuery ML stores these transformations with the model and automatically reapplies them during ML.PREDICT, so dashboard queries can run predictions on raw records without repeating the logic. External pipelines, materialized views, or delegating encoding to dashboards would require manual coordination and risk feature skew, whereas BigQuery ML does not offer an auto_preprocess flag in CREATE MODEL.