You're packaging a Snowflake Native Application that performs complex analytical computations on data within the consumer's account. This computation involves several intermediate tables and functions, all created within the application package. You want to optimize the application's performance and reduce storage costs in the consumer's account. Which of the following strategies can be employed to achieve these goals, especially considering that intermediate data is not intended to be directly accessible to the consumer?
Correct Answer: B,C
Options B and C are correct because they both contribute to optimizing performance and reducing storage costs without compromising data privacy. Transient tables (Option B) reduce storage costs by eliminating Time Travel and Fail-safe, while still allowing for persistence within the consumer's account. Data pruning (Option C) directly reduces the amount of data stored by deleting intermediate results as soon as they are no longer needed. Using temporary tables (Option A) might not be suitable if the application's computation spans multiple sessions or contexts. Using external tables (Option D) would introduce additional complexity and overhead related to data transfer and external storage management. Relying solely on Snowflake's automatic optimization features (Option E) might not be sufficient to minimize storage costs, especially for large intermediate datasets.