Google Cloud Associate Data Practitioner — Question 7

You have millions of customer feedback records stored in BigQuery. You want to summarize the data by using the large language model (LLM) Gemini. You need to plan and execute this analysis using the most efficient approach. What should you do?

Answer options

• A. Query the BigQuery table from within a Python notebook, use the Gemini API to summarize the data within the notebook, and store the summaries in BigQuery.
• B. Use a BigQuery ML model to pre-process the text data, export the results to Cloud Storage, and use the Gemini API to summarize the pre- processed data.
• C. Create a BigQuery Cloud resource connection to a remote model in Vertex Al, and use Gemini to summarize the data.
• D. Export the raw BigQuery data to a CSV file, upload it to Cloud Storage, and use the Gemini API to summarize the data.

Correct answer: C

Explanation

The correct answer is C because it allows direct integration with Vertex AI, enabling efficient summarization using Gemini. Option A is less efficient due to the intermediate step of using a notebook, while B adds unnecessary complexity by exporting pre-processed data. Option D involves multiple steps of exporting and uploading data, which is not as streamlined as using a direct connection.