Test Data Management Software for smart
Optimize your QA and development processes with test data management and provisioning software: secure, scalable, and aligned with GDPR requirements
Manage test data automatically and securely
Classify
Automatically identify and tag sensitive data in your sources to apply transformation rules from the start of the process
Provide
Deliver ready-to-use datasets to your development and QA environments, maintaining structural and logical integrity
Automate
Manage the entire test data provisioning cycle from a single platform, speeding up workflows and reducing manual tasks
How Gigantics handles sensitive data
Data classification
Data transformation
Data provisioning

Share anonymized test data across development and testing environments
Facilitate dataset delivery from your databases to non-production environments, DevOps pipelines, or external teams—ensuring data protection and accelerating validation workflows


Test data use cases for QA and development environments
Implement functional, integration, and migration tests using anonymized data that reflects real structures
Ensure consistency across environments, speed up release validation, and strengthen your compliance strategy without exposing sensitive information
UI Testing
Validate the user experience by simulating real-world scenarios in test environments with anonymized and coherent data structures
SQL Optimization
Run performance and accuracy tests on your SQL queries using realistic and consistent test data—without accessing production
Data migration testing
Ensure data integrity and privacy during migrations between databases or schema versions, using prepped datasets for testing
End-to-end integration testing
Simulate production environments with secure data to validate interoperability between services, apps, and architecture layers
Agile environment provisioning
Spin up temporary development or testing environments using ready-to-use test data—without relying on manual processes or IT
Data simulation for analytics
Use anonymized test data to run analytics, dashboards, or business simulations without compromising data confidentiality
Secure test data sharing
Share datasets internally or with third parties without exposing sensitive data, using anonymization techniques and access control
AI & ML model training
Train algorithms with test data that replicates the structure and behavior of real data, ensuring result quality and regulatory compliance
