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Generative AI Leader Practice Question: A financial analyst wants to run a regression…
A financial analyst wants to run a regression model inside BigQuery using SQL, without moving data to a separate ML environment. Which Google Cloud service allows this directly?
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
✓
BigQuery ML
BigQuery ML enables creating and running ML models using standard SQL queries directly in BigQuery. Vertex AI and AI Platform require data to be moved, and AutoML is a higher-level service but still not SQL-based.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
BigQuery ML
Why this is correct
BigQuery ML trains and runs regression models directly against BigQuery tables using SQL statements such as CREATE MODEL, so the analyst never exports data to a separate ML environment. This in-database execution is precisely what satisfies the stem's no-data-movement constraint.
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AI Platform
Why it's wrong here
AI Platform is the predecessor to Vertex AI and likewise operates as a separate ML environment, not as SQL functions executing within BigQuery. It is tempting because it historically provided managed training and prediction services, and would be correct for legacy custom model workflows hosted outside the data warehouse.
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AutoML Tables
Why it's wrong here
AutoML Tables trains and deploys models from a separate managed environment; it does not execute regression inside BigQuery via SQL statements. It is tempting because it targets tabular data and requires no coding, and would be correct when building custom models on structured datasets outside BigQuery.
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Vertex AI
Why it's wrong here
Vertex AI is a separate ML platform requiring data export or pipeline construction; it does not run regression directly in BigQuery through SQL. It is tempting because it offers end-to-end model training and deployment, and would be correct for custom model development, pipelines and MLOps beyond BigQuery's built-in functions.
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This Generative AI Leader practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Generative AI Leader exam.