Use a basic SQL script to identify and remove duplicate customer records without further analysis.

Develop a comprehensive data validation framework that includes checks for data type consistency, removal of outliers, correction of data entry errors, and validation against international data protection standards.

Automatically exclude any transaction records that do not match predefined criteria, without manual review or consideration for data recovery.

Assign a team to manually inspect each record for accuracy and compliance, despite the volume of data.