A. Create a relational table with predefined columns based on the expected schema. Use a COPY INTO statement to load the data, handling schema variations through error handling in the COPY INTO statement.

B. Create a VARIANT column in a Snowflake table. Load the JSON data into the VARIANT column using a COPY INTO statement. Query the data using dot notation and FLATTEN function as needed.

C. Create an external table using the CREATE EXTERNAL TABLE command, pointing to the external stage.
Define a schema on the external table based on a representative JSON file. Query the data directly from the external table.

D. Use a stored procedure to parse the JSON files and insert the data into a relational table with a predefined schema. Implement error handling within the stored procedure to handle schema variations.

E. Load the JSON data into a cloud storage location, then use a Spark cluster to process and transform the data into a structured format before loading it into Snowflake.