The Information Schema and Account Usage Share in Snowflake provide metadata and historical usage data for various objects within a Snowflake account. Specifically, they offer storage information for Tables, Databases, and Internal Stages. These schemas contain views and table functions that allow users to query object metadata and usage metrics, such as the amount of data stored and historical activity.
* Tables: The storage information includes data on the daily average amount of data in database tables.
* Databases: For databases, the storage usage is calculated based on all the data contained within the database, including tables and stages.
* Internal Stages: Internal stages are locations within Snowflake for temporarily storing data, and their storage usage is also tracked.
References: The information is verified according to the SnowPro Core Certification Study Guide and Snowflake documentation

The purpose of a Query Profile is to provide a detailed analysis of a particular query's execution plan, including the mechanics, behavior, and performance. It helps in identifying potential performance bottlenecks and areas for optimization

When a pipe is recreated using the CREATE OR REPLACE PIPE command, the load history of the pipe is reset. This means that Snowpipe will consider all files in the stage as new and will attempt to load them, even if they were loaded previously by the old pipe2.

Snowpipe via REST API can reference both named internal stages within Snowflake and external stages, such as Amazon S3, Google Cloud Storage, or Microsoft Azure1. This means that Snowpipe is not limited to only external stages as a source for data loading.
References = [COF-C02] SnowPro Core Certification Exam Study Guide, Snowflake Documentation1 Reference: https://community.snowflake.com/s/article/Making-Transient-table-by-Default

A VARIANT column in Snowflake can store semi-structured data types. This includes:
* B. OBJECT: An object is a collection of key-value pairs in JSON, and a VARIANT column can store this type of data structure.
* D. ARRAY: An array is an ordered list of zero or more values, which can be of any variant-supported data type, including objects or other arrays.
The VARIANT data type is specifically designed to handle semi-structured data like JSON, Avro, ORC, Parquet, or XML, allowing for the storage of nested and complex data structures.
References:
* Snowflake Documentation on Semi-Structured Data Types
* SnowPro Core Certification Study Guide