Google Cloud Associate Data Practitioner — Question 62

Your team uses the Google Ads platform to visualize metrics. You want to export the data to BigQuery to get more granular insights. You need to execute a one-time transfer of historical data and automatically update data daily. You want a solution that is low-code, serverless, and requires minimal maintenance. What should you do?

Answer options

• A. Export the historical data to BigQuery by using BigQuery Data Transfer Service. Use Cloud Composer for daily automation.
• B. Export the historical data to Cloud Storage by using Storage Transfer Service. Use Pub/Sub to trigger a Dataflow template that loads data for daily automation.
• C. Export the historical data as a CSV file. Import the file into BigQuery for analysis. Use Cloud Composer for daily automation.
• D. Export the historical data to BigQuery by using BigQuery Data Transfer Service. Use BigQuery Data Transfer Service for daily automation.

Correct answer: D

Explanation

The correct answer, D, is appropriate because it leverages the BigQuery Data Transfer Service for both the one-time historical data transfer and the daily updates, ensuring a streamlined and serverless solution. Option A introduces Cloud Composer, which adds complexity and maintenance. Option B involves additional components like Cloud Storage and Dataflow, which complicate the process. Option C requires manual steps for the CSV import, making it less efficient and more maintenance-intensive.