Location
https://www.kennesaw.edu/ccse/events/computing-showcase/sp25-cday-program.php
Document Type
Event
Start Date
15-4-2025 4:00 PM
Description
In today’s data-driven world, organizations handle vast amounts of sensitive information, including personally identifiable information (PII), health records, and financial data. For institutions like schools, this data often includes sensitive details about students, parents, and staff, making data protection not just important, but critical. With increasing privacy regulations such as GDPR and HIPAA, organizations must implement robust measures to protect this information while still enabling its use for legitimate purposes like testing, analytics, and development. Our web-based data masking tool addresses this need by allowing organizations to protect sensitive data without compromising its usability. By applying dynamic masking rules to relational databases and generating masked data extracts, the tool ensures compliance with privacy laws while improving operational efficiency. It automates data protection processes and generates realistic, anonymized data, allowing organizations to securely manage and share sensitive information for non-production purposes. Designed for scalability and ease of use, the tool helps organizations streamline their data protection workflows while maintaining the integrity of their testing and analytical environments.
UC-019 Gwinnett County Public Schools - Data Masking Tool
https://www.kennesaw.edu/ccse/events/computing-showcase/sp25-cday-program.php
In today’s data-driven world, organizations handle vast amounts of sensitive information, including personally identifiable information (PII), health records, and financial data. For institutions like schools, this data often includes sensitive details about students, parents, and staff, making data protection not just important, but critical. With increasing privacy regulations such as GDPR and HIPAA, organizations must implement robust measures to protect this information while still enabling its use for legitimate purposes like testing, analytics, and development. Our web-based data masking tool addresses this need by allowing organizations to protect sensitive data without compromising its usability. By applying dynamic masking rules to relational databases and generating masked data extracts, the tool ensures compliance with privacy laws while improving operational efficiency. It automates data protection processes and generates realistic, anonymized data, allowing organizations to securely manage and share sensitive information for non-production purposes. Designed for scalability and ease of use, the tool helps organizations streamline their data protection workflows while maintaining the integrity of their testing and analytical environments.
