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A company wants to predict future sales trends based on historical transactional data, seasonal patterns, and promotional activities. They have their historical sales data stored in BigQuery and prefer to use SQL for their analysis and model training to leverage existing skills within their analytics team. Which Google Cloud service enables them to build and execute machine learning models directly within their data warehouse using SQL?
- ABigQuery ML
- BDataproc
- CVertex AI Workbench
- DCloud SQL
Show answer & explanationAnswer & explanation
Correct answer: A. BigQuery ML
BigQuery ML allows users to create and execute machine learning models using standard SQL queries directly within BigQuery, eliminating the need to export data or learn new programming languages.
Why the other options are wrong
- B. Dataproc is a managed Hadoop/Spark service, primarily for large-scale data processing, not for building ML models directly with SQL in a data warehouse.
- C. Vertex AI Workbench is a notebook environment for ML development, requiring Python/R, not SQL for model building.
- D. Cloud SQL is a relational database and does not have integrated ML capabilities for building models with SQL.
BigQuery ML
A feature of BigQuery that allows users to create and execute machine learning models using standard SQL queries.
- Leverages existing SQL skills for ML
- No data export required, models trained directly in BigQuery
- Supports various model types like linear regression, logistic regression, k-means, ARIMA
Memory trick: Big data needs BigQuery ML for SQL-powered insights.