Exam Cloud Digital Leader topic 1 question 38 discussion

BigQuery ML lets you create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by letting SQL practitioners build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data. https://cloud.google.com/bigquery-ml/docs/introduction

Your organization should choose **BigQuery ML (Option A)** because it enables users with SQL skills to create and run machine learning models directly within BigQuery using SQL queries https://cloud.google.com/bigquery/docs/bqml-introduction

A is correct

BigQuery ML is a machine learning service that makes it easy for anyone to create and train machine learning models, even if they don't have a lot of machine learning experience. BigQuery ML is built on top of BigQuery, so you can use your existing database skills to train and deploy machine learning models.

A is correct

BigQuery ML is a feature of Google BigQuery that allows you to build and deploy machine learning models using SQL queries directly within the BigQuery environment. It enables data analysts and database developers to utilize their existing SQL skills for machine learning tasks without requiring advanced machine learning expertise. By using BigQuery ML, your team can leverage their database skills and work within the familiar SQL environment to build and deploy machine learning models for predicting visitor behavior. This eliminates the need for advanced machine learning knowledge and enables a smooth transition from data analysis to machine learning tasks.

A. BigQuery ML

Keywords: predict, ML model, database skills

BigQuery have some ML functions

Build model

build models using queries.

BigQuery ML

BigQuery ML

A. BigQuery ML

BigQuery ML

A is the answer