To find customers whose last names start with "Mc" or "MC", we need to ensure our SQL query correctly identifies and compares these prefixes regardless of case variations. Let's analyze the given options:
* Option B: WHERE UPPER(SUBSTR(cust_name, INSTR(cust_name, ' ') + 1)) LIKE UPPER(' MC%')This clause uses UPPER to convert both the extracted substring (starting just after the first space, assuming it indicates the start of the last name) and the comparison string 'MC%' to uppercase.
This ensures case-insensitive comparison. The LIKE operator is used to match any last names starting with "MC", which will correctly capture both "Mc" and "MC". This option is correct.
* Option C: WHERE INITCAP(SUBSTR(cust_name, INSTR(cust_name, ' ') + 1)) LIKE 'Mc%' This clause applies INITCAP to the substring, which capitalizes the first letter of each word and makes other letters lowercase. The result is compared to 'Mc%', assuming only the last name follows the space.
This approach will match last names starting with "Mc" (like "McEwen"), but not "MC". However, considering we're looking for "Mc" specifically, this clause works under the assumption that "Mc" is treated as proper capitalization for these last names. Thus, it can also be considered correct, albeit less inclusive than option B.
The other options either use incorrect syntax or apply case-sensitive matches without ensuring that both "Mc" and "MC" are captured:
* Option A: Contains syntax errors (unmatched quotes and wrong use of IN).
* Option D: Uses case-sensitive match without combining both "Mc" and "MC".
* Option E: Only matches "Mc", which is too specific.

C: True. You can add a new NOT NULL column to an existing table, provided you specify a DEFAULT value for the column. This ensures that existing rows in the table can be updated with a default value, thus maintaining the NOT NULL constraint integrity.
E: True. It is permissible to increase the width of a numeric column, provided the change does not truncate existing data. This change is generally safe as it allows for greater values or more precision without affecting existing data.
F: True. The default value of a column can be changed. This action affects subsequent insert operations but does not alter the values of existing rows. Changing the default is useful for adapting tables to evolving business rules without impacting existing data.