Q. You are building storage for files for a data pipeline on Google Cloud. You want to support JSON files. The schema of these files will occasionally change. Your analyst teams will use running aggregate ANSI SQL queries on this data. What should you do? A. Use BigQuery for storage. Provide format files for data load. Update the format files as needed. B. Use BigQuery for storage. Select “Automatically detect” in the Schema section. C. Use Cloud Storage for storage. Link data as temporary tables in BigQuery and turn on the “Automatically detect” option in the Schema section of BigQuery. D. Use Cloud Storage for storage. Link data as permanent tables in BigQuery and turn on the “Automatically detect” option in the Schema section of BigQuery. Answer: B Feedback B is correct because of the requirement to support occasionally (schema) changing JSON files and aggregate ANSI SQL queries: you need to use BigQuery, and it is quickest to use ‘Automatically detect’ for schema changes. A is not correct because you should not provide format files: you can simply turn on the ‘Automatically detect’ schema changes flag. C and D are not correct because you should not use Cloud Storage for this scenario: it is cumbersome and doesn’t add value. Q. Your infrastructure includes two 100-TB enterprise file servers. You need to perform a one-way, one-time migration of this data to the Google Cloud securely. Only users in Germany will access this data. You want to create the most cost-effective solution. What should you do? A. Use Transfer Appliance to transfer the offsite backup files to a Cloud Storage Regional storage bucket as a final destination. B. Use Transfer Appliance to transfer the offsite backup files to a Cloud Storage Multi-Regional bucket as a final destination. C. Use Storage Transfer Service