You have a Snowflake table named 'CUSTOMER DATA' with a 'JSON DATA' column containing nested JSON objects. You need to extract specific fields from the nested JSON, transform the data, and load it into a new table named 'CLEANED CUSTOMERS'. You want to automate this process using a task and stream. Which of the following SQL statements, when combined correctly, provide the most efficient and reliable solution for automating this data transformation?

Correct Answer: D
The correct answer (D) uses a stream to capture changes in the 'CUSTOMER_DATX table. The task is chained to the stream using 'AFTER ensuring it runs only when there are changes in the stream. It then inserts the transformed data (name, age) from the stream into 'CLEANED_CUSTOMERS' , filtering based on Options A and C don't leverage streams and will re-process the entire 'CUSTOMER DATA table each time the task runs. Option B uses a MERGE statement without considering any audit columns from the stream and option E sets SHOW INITIAL ROWS = TRUE on stream that are deprecated and doesn't ensure task execution correctly because task doesn't use the stream state properly. A stream is crucial for incremental loading and efficient processing of only the changed data.