Exam: Cloud Digital Leader 0 Likes
Your organization wants to predict the behavior of visitors to its (Digital Leader)
Your organization wants to predict the behavior of visitors to its public website. To do that, you have decided to build a machine learning model. Your team has database-related skills but only basic machine learning skills, and would like to use those database skills.
Which Google Cloud product or feature should your organization choose?
A) BigQuery ML.
B) LookML.
C) TensorFlow.
D) Cloud SQL.
Solution
Correct answer: A) BigQuery ML.
BigQuery ML stands out as the ideal product for your organization. Here's why:
Leverage database skills: BigQuery ML seamlessly integrates with BigQuery, a familiar SQL-based data warehouse. Your team can utilize their existing database expertise to explore data, prepare features, and even build simple models using SQL queries.
Low code ML access: BigQuery ML offers pre-built machine learning models you can easily train and deploy with just SQL statements. This low-code approach empowers your team with basic ML skills to create valuable insights without diving deep into complex coding.
Scalability and automation: BigQuery ML scales effortlessly with your website traffic, automatically managing model training and prediction. This frees your team from infrastructure burden and lets them focus on analyzing results and improving models.
While LookML (B) is great for data visualization, and TensorFlow (C) offers powerful ML capabilities, they require significant coding expertise. Cloud SQL (D) handles relational data but lacks built-in ML features. BigQuery ML bridges the gap, allowing your team to leverage their database skills and gain valuable insights into website visitor behavior with minimal ML coding.
Category: Innovating with data and Google Cloud