Google Cloud Professional Machine Learning Engineer PMLE — Topic 1 Question 281

Question

You work at a large organization that recently decided to move their ML and data workloads to Google Cloud. The data engineering team has exported the structured data to a Cloud Storage bucket in Avro format. You need to propose a workflow that performs analytics, creates features, and hosts the features that your ML models use for online prediction. How should you configure the pipeline?

Accepted Answer

Correct answer: B. The correct answer is B. Option B: Ingest the Avro files into BigQuery to perform analytics. Use a Dataflow pipeline to create the features, and store them in Vertex AI Feature Store for online prediction. BigQuery is a serverless, petabyte-scale data warehouse for fast SQL analytics with no infrastructure to manage. Dataflow runs serverless Apache Beam pipelines for stream and batch data processing with autoscaling. Vertex AI is the unified managed platform to build, train, tune, deploy, and operate ML models.

Google Cloud Professional Machine Learning Engineer PMLE — Question 281