Explanation/Reference: https://interworks.com/blog/bdu/2020/02/05/zero-to-snowflake-secure-data-sharing/

Snowflake supports a variety of subquery types, including both correlated and uncorrelated subqueries. The correct answers are B and E, which highlight Snowflake's flexibility in handling subqueries within SQL queries.
* Uncorrelated Scalar Subqueries: These are subqueries that can execute independently of the outer query. They return a single value and can be used anywhere a value expression is allowed, offering great flexibility in SQL queries.
* EXISTS, ANY/ALL, and IN Subqueries: These subqueries are used in WHERE clauses to filter the results of the main query based on the presence or absence of matching rows in a subquery. Snowflake supports both correlated and uncorrelated versions of these subqueries, providing powerful tools for complex data analysis scenarios.
* Examples and Usage:
* Uncorrelated Scalar Subquery:
SELECT * FROM employees WHERE salary > (SELECT AVG(salary) FROM employees);
* Correlated EXISTS Subquery:
SELECT * FROM orders o WHERE EXISTS (SELECT 1 FROM customer c WHERE c.id = o.customer_id AND c.region = 'North America'); Reference: For comprehensive details on the types of subqueries supported by Snowflake and examples of their usage, consult the Snowflake documentation on subqueries:
https://docs.snowflake.com/en/sql-reference/constructs/subqueries.html

In Snowflake, stored procedures and User-Defined Functions (UDFs) have different invocation patterns within SQL:
* Option B is correct: A single executable statement can call only one stored procedure due to the procedural and potentially transactional nature of stored procedures. In contrast, a single SQL statement can call multiple UDFs because UDFs are designed to operate more like functions in traditional programming, where they return a value and can be embedded within SQL queries.References:
Snowflake documentation comparing the operational differences between stored procedures and UDFs.