PDE Preparing and Using Data for Analysis Practice Question
A data engineer needs to train a linear regression model in BigQuery ML using a table with 10 million rows. The model will predict sales based on features like advertising spend, seasonality, and store location. Which SQL statement should they use to create and train the model?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
CREATE MODEL mymodel OPTIONS(model_type='LINEAR_REG') AS SELECT * FROM sales_data
In BigQuery ML, the CREATE MODEL statement with option MODEL_TYPE='LINEAR_REG' creates a linear regression model. The training data is specified in the AS SELECT clause.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
CREATE MODEL mymodel AS SELECT * FROM sales_data WITH LINEAR REGRESSION
Why it's wrong here
Incorrect syntax.
- ✓
CREATE MODEL mymodel OPTIONS(model_type='LINEAR_REG') AS SELECT * FROM sales_data
Why this is correct
Correct syntax for linear regression in BigQuery ML.
- ✗
CREATE OR REPLACE MODEL mymodel OPTIONS(model_type='LINEAR_REGRESSION') AS SELECT * FROM sales_data
Why it's wrong here
Model type should be 'LINEAR_REG' not 'LINEAR_REGRESSION'.
- ✗
CREATE MODEL mymodel OPTIONS(model_type='linear_reg') AS SELECT * FROM sales_data
Why it's wrong here
The model_type option should be 'LINEAR_REG', not 'linear_reg'.
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