Question

A retail analytics team stores millions of product reviews in a BigQuery table. Analysts who are comfortable with SQL but not with Python want to generate concise one-sentence summaries of each review directly inside their existing BigQuery workflow, without building a custom pipeline or managing serving infrastructure. Which approach best meets these requirements with the least operational overhead?

Accepted Answer

Create a BigQuery ML remote model that references a Vertex AI Gemini endpoint, then call ML.GENERATE_TEXT in a SQL query over the reviews table.

Answer

Export the reviews to Cloud Storage, run a Vertex AI batch prediction job against a Gemini model, and load the summaries back into BigQuery.

Answer

Train a custom text summarization model with AutoML and deploy it to a Vertex AI online endpoint that analysts query via the REST API.

Answer

Build a Dataflow streaming pipeline that reads from BigQuery, calls the Vertex AI SDK for each row, and writes summaries to a new table.