Reader accounts in Snowflake are designed to allow users to read data shared with them but do not have the capability to extract data for use outside of Snowflake. They are intended for consuming shared data within the Snowflake environment only.

When the retention period for an object ends in Snowflake, Time Travel on the historical data is dropped . This means that the ability to access historical data via Time Travel is no longer available once the retention period has expired2.

Query pruning in Snowflake refers to the optimization technique where the system reduces the amount of data scanned by a query based on the query conditions. This typically involves skipping unnecessary data partitions that do not contribute to the query result. The effectiveness of this technique can be observed through:
Option A: Partitions scanned. This statistic indicates how many data partitions were actually scanned as a result of query pruning, showing the optimization in action.
Option C: Bytes scanned. This measures the volume of data physically read during query execution, and a reduction in this number indicates effective query pruning, as fewer bytes are read when unnecessary partitions are skipped.
Options B, D, and E do not directly relate to observing the effects of query pruning. "Partitions total" shows the total available, not the impact of pruning, while "Bytes read from result" and "Bytes written" relate to output rather than the efficiency of data scanning.
Reference: Snowflake documentation on performance tuning and query optimization techniques, specifically how query pruning affects data access.

Valid sub-clauses to the OVER clause for a window function in SQL are:
C . ORDER BY: This clause specifies the order in which the rows in a partition are processed by the window function. It is essential for functions that depend on the row order, such as ranking functions.
D . PARTITION BY: This clause divides the result set into partitions to which the window function is applied. Each partition is processed independently of other partitions, making it crucial for functions that compute values across sets of rows that share common characteristics.
These clauses are fundamental to defining the scope and order of data over which the window function operates, enabling complex analytical computations within SQL queries.
Reference:
Snowflake Documentation: Window Functions

Snowflake supports several methods for authenticating users, including federated authentication, key-pair authentication, and OAuth. Federated authentication allows users to authenticate using their organization's identity provider. Key-pair authentication uses a public-private key pair for secure login, and OAuth is an open standard for access delegation commonly used for token-based authentication. Reference: Authentication policies | Snowflake Documentation, Authenticating to the server | Snowflake Documentation, External API authentication and secrets | Snowflake Documentation.