Snowflake SnowPro Certification Practice Test

When creating a file format in Snowflake, several options are relevant to how data will be structured and stored, making the selection of schema name, file format type, compression method, and column separator essential.

The schema name is used to organize the data within a specific context, enabling better management and access. The file format type dictates how Snowflake interprets the data, with common types including CSV, JSON, AVRO, PARQUET, and ORC. Each of these formats has its own set of structured characteristics that are suitable for different types of data.

The compression method is crucial for optimizing storage and improving performance by reducing the amount of disk space required. Various methods can be chosen, such as GZIP or LZ4, each having its advantages depending on the use case.

Lastly, the column separator is vital when dealing with delimited formats (like CSV) since it defines how the data values are separated within the file. By specifying these details, users ensure that Snowflake can accurately interpret and process the incoming data.

Other options listed focus on fewer aspects or include irrelevant parameters, which do not fully capture the comprehensive capabilities of file formats in Snowflake. Therefore, the options provided in the correct choice encompass the necessary components to