Data masking is a technique used to protect sensitive information by replacing real data with fictitious, obfuscated, or masked data in non-production environments while maintaining the data's usability for testing, development, or analytics purposes. This process helps organizations comply with data privacy regulations such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA) by preventing unauthorized access to sensitive data. Data masking techniques include encryption, tokenization, scrambling, and anonymization, which obscure sensitive data elements such as personally identifiable information (PII), credit card numbers, and social security numbers. Masked data retains the format and structure of the original data, allowing applications to function normally while protecting sensitive information from unauthorized access or disclosure. Data masking is a crucial component of data security strategies, ensuring the confidentiality and integrity of sensitive data in non-production environments.