Challenge: Build a Robust Data Processing Script

Combine everything you have learned about validation, exceptions, and safe execution to build a robust data processing script. In this challenge, you will process a batch of data rows, validate each entry, and handle any issues gracefully using exceptions and error logging.

• Validate each data row to ensure the name field is present and not empty, and that the age field is an integer between 0 and 120.
• If validation fails, throw a DataValidationException with a descriptive message.
• In the importData function, catch any DataValidationException and throw a DataImportException that includes the original validation error message.
• In the main processing loop, catch DataImportException and log the error message using the logError function.
• If data passes validation, return a string in the format "Imported: {name} ({age})".