Explanation:
The best approach is to use BigQuery as a data warehouse and set output destinations for caching large queries. BigQuery is a fully managed data warehouse designed to scale and handle massive datasets efficiently. It supports SQL queries and provides a low-maintenance architecture, making it suitable for analyzing large result sets of medical information. Options such as Cloud SQL, Cloud Spanner, and self-managed MySQL may not scale as cost-effectively for 10TB+ data volumes and would require more maintenance. Therefore, the optimal solution here is leveraging BigQuery.
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Your healthcare organization needs to efficiently retrieve substantial result sets of medical information from the existing system, which contains a database exceeding 10 TBs. This retrieved data should be stored in new tables to facilitate further queries. The solution for the database must feature a low-maintenance architecture, be accessible through SQL, and support data analytics on large result sets economically. What approach should you take to achieve this?
A
Use Cloud SQL, but first organize the data into tables. Use JOIN in queries to retrieve data.
B
Use BigQuery as a data warehouse. Set output destinations for caching large queries.
C
Use a MySQL cluster installed on a Compute Engine managed instance group for scalability.
D
Use Cloud Spanner to replicate the data across regions. Normalize the data in a series of tables.