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GCP Professional Data Engineer Practice Question

A telecom company is building a BigQuery ML model that predicts customer churn from 150 numeric usage metrics. Model accuracy degrades because extreme magnitude differences across columns dominate the loss function. Data engineers decide to add an explicit preprocessing step in the CREATE MODEL statement instead of relying on automatic feature standardization. Which manual preprocessing function should they call in the TRANSFORM clause to scale every numeric feature to unit L2 norm without changing the feature count?

  • ML.NORMALIZER

  • ML.ONE_HOT_ENCODER

  • ML.MAX_ABS_SCALER

  • ML.ROBUST_SCALER

GCP Professional Data Engineer
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