What is data masking in the context of cybersecurity, and which platforms are best for using it?

Although it may seem unrealistic, data masking—a formal term for the addition of functional value to the same set that appears differently—is a crucial strategy across data platforms. As a reminder, its market value is expected to reach USD 1268 million by 2028, making it a differentiator when selecting the best tool. Before I go into those strategies, let me explain what data masking is and the best practices are. Data masking is a technique that protects sensitive data by rendering it unidentifiable and immutable to unauthorized users. It is crucial for maintaining consistency and usability across multiple databases. The goal of creating a functional substitute is to use it as a means of identifying sensitive information.