When two organizations discuss a potential merger, securely sharing sensitive payroll data is crucial. Data masking offers the best solution to protect employee information while enabling CFOs to compare pay scales across roles. Learn how data masking ensures data privacy and facilitates successful information sharing during the merger process.
Table of Contents
Question
Two organizations are discussing a possible merger. Both organizations’ Chief Financial Officers would like to safely share payroll data with each other to determine if the pay scales for different roles are similar at both organizations. Which of the following techniques would be best to protect employee data while allowing the companies to successfully share this information?
A. Pseudo-anonymization
B. Tokenization
C. Data masking
D. Encryption
Answer
C. Data masking
Explanation
C. Data masking is the best technique to protect employee data while allowing the companies to successfully share payroll information during merger discussions. Data masking involves replacing sensitive data with fictitious but realistic data that maintains the original data format and structure. This enables the CFOs to analyze and compare pay scales for different roles without exposing actual employee information.
Data masking preserves data privacy by obfuscating sensitive details such as employee names, addresses, social security numbers, and exact salaries. The masked data retains the essential characteristics and relationships within the dataset, ensuring that the analysis remains accurate and meaningful.
By employing data masking, the organizations can securely share payroll data, comply with data protection regulations, and maintain employee confidentiality throughout the merger assessment process. This technique strikes a balance between safeguarding sensitive information and enabling necessary data sharing for informed decision-making.
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