A. Use `PARSE DOCUMENT with default settings and load the raw JSON output into a VARIANT column in a Snowflake table. Implement custom SQL queries to extract the desired information from the VARIANT data.

B. Use `PARSE DOCUMENT with a pre-defined JSON schema to enforce a rigid structure on the extracted data, and load the output directly into a relational table with predefined columns for name, address, and phone number.

C. Create a custom UDF (User-Defined Function) that calls 'PARSE_DOCUMENT and then uses regular expressions or other text processing techniques to extract the desired information from the raw text output. Load the extracted data into a relational table.

D. Employ a combination of 'PARSE DOCUMENT and Snowflake's external functions to integrate with a third-party OCR service for enhanced text extraction. Post-process the results using SQL to load structured data into a table. Use 'MAX FILE SIZE=16777216' while calling parse document

E. Directly load PDF files into a relational table's TEXT column and write SQL queries utilizing LIKE and SUBSTRING functions to extract invoice details. Use 'MAX FILE SIZE-16777216' while loading pdf