Data masking techniques are methods used to protect sensitive information by replacing it with fictional or scrambled data. This ensures that the original data remains confidential while still allowing for its use in testing, development, or analysis. Common techniques include substitution, where real data is replaced with similar-looking values, and shuffling, which rearranges data within a dataset to obscure its original context. Another technique is encryption, which transforms data into a coded format that can only be read with a specific key. Additionally, tokenization replaces sensitive data with unique identifiers or tokens, allowing for secure data handling without exposing the actual information. These techniques help organizations comply with data protection regulations while maintaining data utility.