A. Use before the insert statement to identify invalid rows, then filter those rows out using a WHERE clause in the INSERT statement.

B. Create a file format with `ON ERROR = 'SKIP_FILE", and Snowflake will automatically skip the file if it encounters an error. Then insert into target table.

C. Use in the INSERT statement. Rows with invalid date formats will result in NULL values for the
'SALE_DATE column, and the insert operation will continue. Then filter out rows where SALE DATE is NULL using a WHERE clause.

D. Use the function with a custom date format. If TO_DATE fails, it will throw an error and abort the insert operation but this is undesirable. There isn't a way to tell TO DATE to skip errors.

E. Create an error table and specify 'ON_ERROR = 'CONTINUE" file format option, then use
'TO_DATE function with a custom date format and then load data. Once loading is done, query error table to find the bad records.