Snowflake's virtual warehouses are responsible for query execution.They are clusters of compute resources that execute SQL statements, perform DML operations, and load data into tables

The Query Profile in Snowflake is used to identify performance issues with queries. Common issues that can be found using the Query Profile include identifying inefficient micro-partition pruning (D) and data spilling to a local or remote disk (E).Micro-partition pruning is related to the efficiency of query execution, and data spilling occurs when the memory is insufficient, causing the query to write data to disk, which can slow down the query performance1.

The VALIDATION_MODE parameter can be used with the COPY command to verify data files without loading them into the specified table.This parameter allows users to check for errors in the files

Micro-partitions in Snowflake are immutable objects, which means once they are written, they cannot be modified. This immutability supports the use of Time Travel, allowing users to access historical data within a defined period. Additionally, micro-partitions can significantly reduce the amount of I/O from object storage to virtual warehouses. This is because Snowflake's query optimizer can skipover micro-partitions that do not contain relevant data for a query, thus reducing the amount of data that needs to be scanned and transferred.
References: [ COF-C03 ] SnowPro Core Certification Exam Study Guide
https://docs.snowflake.com/en/user-guide/tables-clustering-micropartitions.html