Data Masking

Data Masking is an essential technique for ensuring that sensitive information within a database is safeguarded, while still preserving the usability of data for authorized operations. Data masking focuses on protecting personally identifiable information (PII), financial details, and other confidential data, ensuring compliance with privacy regulations and internal governance policies. It involves a systematic approach to anonymizing and obfuscating data using strategies such as substitution, shuffling, or encryption. By transforming real data into fictitious yet realistic values, data masking ensures that sensitive information is not exposed during testing, analytics, or data sharing. Through this approach, organizations can balance data utility and security, enabling safer data handling across development, testing, and business processes.

Common data masking approaches include:

• Static Data Masking (SDM): Involves creating a masked copy of the original data in non-production environments. 

• Dynamic Data Masking (DDM): Dynamically hides sensitive data at query time based on user roles or permissions without modifying the original database. Users only see masked values.