Select the different types of Internal Stages: (Choose three.)
Select the different types of Internal Stages: (Choose three.)
There are three main types of internal stages in Snowflake: Named Stage, User Stage, and Table Stage. Named stages are explicitly created storage locations; User stages are unique to each user for their data loading needs; Table stages are associated with specific database tables for data loading and unloading.
True or False: A customer using SnowSQL / native connectors will be unable to also use the Snowflake Web Interface (UI) unless access to the UI is explicitly granted by support.
A customer using SnowSQL or native connectors is also able to use the Snowflake Web Interface (UI) without requiring explicit access granted by support. Both SnowSQL and the Web Interface are accessible to all users by default unless specific restrictions are configured by an administrator.
Account-level storage usage can be monitored via:
Account-level storage usage can be monitored through The Snowflake Web Interface (UI) in the Account -> Billing & Usage section. This interface provides a comprehensive view of storage costs and usage metrics, which allows administrators to track their account's storage consumption. The given reference indicates that this section is designed for monitoring billing and usage, making this option the most appropriate choice for the task described.
Credit Consumption by the Compute Layer (Virtual Warehouses) is based on: (Choose two.)
Credit Consumption by the Compute Layer (Virtual Warehouses) is based on the warehouse size and the number of clusters for the warehouse. Warehouse size (such as XS, S, M, etc.) determines how much computational power is used, and the number of clusters impacts how those computations are distributed, especially in multi-cluster configurations. The number of users and the amount of data processed do not directly influence credit consumption.
Which statement best describes `clustering`?
Clustering represents the way data is grouped together and stored within Snowflake's micro-partitions. This process is intrinsic to how Snowflake manages data storage and retrieval efficiency, enabling faster query performance by reducing the need to scan unnecessary micro-partitions.