Garda Data Masking

Data Masking: 8 Critical Questions Businesses and Developers Ask About Protecting Sensitive Data

Garda expert Dmitry Larin addresses common challenges in data masking during a recent webinar titled 'Data Masking: Battle of Opinions'. The discussion covers why masking remains essential even when encryption is deployed, how to preserve application functionality after anonymization, and the performance trade-offs of processing large databases such as 5 TB PostgreSQL instances. Different masking types including static, dynamic, selective, and streaming are explained with specific use cases for DevOps pipelines, external contractors, and BI systems. The article also examines why machine learning alone is insufficient for discovering personal data and why custom scripts fail at scale across heterogeneous environments like PostgreSQL and Oracle. Practical recommendations include combining masking with encryption, using deterministic transformations for deduplication, and separating replication from masking tasks to avoid production impact.