You are preparing to load data from an internal stage that contains multiple CSV files into a Snowflake table. You need to ensure that only files matching a specific pattern are loaded (e.g., files starting with 'sales_'). You also need to transform the date column (located in the third position of each CSV file) from 'YYYYMMDD' to 'YYYY-MM-DD' format during the load. The target table 'SALES has columns 'product_id', and 'region'. Which combination of options correctly filters the files and transforms the date format during the load process?

Correct Answer: D
Option D is correct. It uses the 'PATTERN' parameter to filter files starting with 'sales_' and ending with '.csv'. It then uses the TRANSFORM AS SELECT clause to select and transform the data. Inside the select clause, it correctly uses 'substr' to reformat the date and 'TO_DATE to convert the re-formatted string into a DATE datatype. The 'ON_ERROR = 'SKIP_FILE" is a good practice for handling potential errors. Option A has an invalid parameter declaration within the COPY INTO command and does not use PATTERN, making the filter inaccurate. Option B attempts to define date format at file format level, but date transformatinon is required and FILES filter declaration is invalid. Option C uses 'TRANSFORMATION' instead of 'TRANSFORM AS SELECT , which is incorrect and will cause an error. Option E attempts to define DATE FORMAT with the wrong TYPE and is missing concatination of DATE string.