Dataguise provided automated discovery and protection of sensitive data across enterprise environments, enabling organizations to maintain compliance with privacy regulations while securing PII and other confidential information.
Last updated Mar 7, 2026 by AI Enrichment
Enterprise data protection and privacy compliance provider acquired by Informatica
Dataguise was a data security software company that provided solutions for discovering, protecting, and managing sensitive data across enterprise environments. The company specialized in data masking, tokenization, and sensitive data discovery to help organizations comply with privacy regulations like GDPR, CCPA, and HIPAA. Dataguise's platform enabled enterprises to identify personally identifiable information (PII), protected health information (PHI), and other sensitive data across structured and unstructured data sources, then apply appropriate protection mechanisms. While Dataguise operated primarily in the data security and privacy space rather than traditional advertising technology, its solutions had relevance to AdTech companies that needed to protect consumer data while maintaining compliance with privacy regulations. The company served enterprise customers across financial services, healthcare, retail, and other data-intensive industries. Dataguise was acquired by Informatica in 2020, with its technology and capabilities integrated into Informatica's broader data management and governance platform. The acquisition strengthened Informatica's data privacy and protection offerings, particularly around sensitive data discovery and masking capabilities that became increasingly critical as privacy regulations expanded globally.
Platform for sensitive data discovery, classification, and protection across databases, big data, and cloud environments
Dynamic and static data masking capabilities to protect sensitive information in non-production environments
Automated discovery and classification of PII, PHI, and other sensitive data across structured and unstructured sources
Format-preserving tokenization to protect sensitive data while maintaining usability