Data Masking

Data masking is used to protect sensitive data that would negatively impact an organization if it were to leak. This could include personal information, such as social security numbers or personal addresses, or confidential business data, like operational plans or blueprints.

There are several ways data can be masked. Examples include

  • Substitution: substituting real information with realistic, but fake information
  • Shuffling: randomly rearranging data within a dataset
  • Encryption: converting data into an unreadable format, readable only by those who are allowed access
  • Character Masking: replacing characters in sensitive data with characters such as “*” or “x”
  • Redaction: commonly seen in legal documents, removing or blacking out sensitive information while leaving the rest readable and intact

Data masking is vital for any company working with sensitive information, whether that be personal information or business information. Strong data masking allows the organization to keep the information private and secure while still using the data for analysis and development.

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