Production-Quality Test Data in Db2 for Comprehensive Testing
Synthesized provides the only AI-driven database masking, subsetting, and generation for Db2, tailored for application development and testing teams. Ensure compliance, and generate production-like data for development and testing environments in half the time.
Why synthesized for DB2 Test data management
Automated data provisioning
for Db2
Robust development and testing
Synthesized ensures rapid detection, root cause analysis, and resolution of data quality issues, enabling quick mitigation before impacting your operations. Feel confident in your application by finding the root cause before anyone else.
Automated full data coverage
Cover a wide range of common data quality issues with our automated data generation scenarios.
Find “unknown unknowns”
Manual data generation rules and thresholds can only go so far. AI-based data generation finds the issues you didn’t plan for in advance.
Meet rigorous regulatory compliance standards
Restrict the use of production sensitive data (customer names, contact information, PCI, or PHI data) by anyone, externalor internal, who does not need access to the data to do their job.
Quick access to data snapshots
Test data at scale across industries
Fraud Detection Testing
Testing teams can use Synthesized to generate diverse and realistic databases that simulate various fraud scenarios. This allows banks to rigorously test their fraud detection systems and algorithms, ensuring robust protection against fraudulent activities.
Regulatory Reporting
By creating compliant synthetic data, Synthesized helps testing and QA teams validate reporting systems to ensure accuracy and adherence to financial regulations such as Basel III and Dodd-Frank.
Claims Processing
Synthesized produces realistic test data for claims processing systems, allowing testing teams to validate and optimize workflows, ensuring efficient and accurate claims handling.
Policy Management
Insurers use Synthesized to generate synthetic data for testing policy management systems, ensuring they can handle various policy scenarios and changes without errors.
Provision reliable data subset
AI-enhanced data masking
Synthesized employs AI algorithms to intelligently select and provision data subsets that closely resemble production environments, ensuring that development and testing activities are conducted with realistic and representative datasets.
Efficient resource utilization
By generating right-sized data subsets tailored to specific use cases, Synthesized optimizes resource utilization in development environments, minimizing wastage and improving efficiency.
Seamless Integration with Cloud Environments
Synthesized seamlessly integrates with cloud platforms to create ephemeral databases for development and testing purposes, offering a cost-effective alternative to using production databases in the cloud.
See documentation
Preserve data consistency
AI-powered data consistency
Synthesized leverages AI to preserve data consistency across development environments, ensuring that provisioned data accurately reflects the state of production datasets.
Transactional data operations
Synthesized supports transactional data operations to maintain data consistency during provisioning processes, guaranteeing reliable and reproducible results.
Dynamic data refresh
Synthesized offers dynamic data refresh capabilities to keep provisioned datasets synchronized with changes in production data, minimizing discrepancies and ensuring up-to-date testing environments.
See documentation
Protect customer data privacy
AI-enhanced data masking
Synthesized utilizes AI-enhanced data masking techniques to anonymize and protect sensitive customer data, safeguarding privacy while maintaining data utility for development and testing purposes.
Role-based access control integration
Synthesized integrates role-based access control mechanisms to restrict access to sensitive customer data, ensuring compliance with regulatory standards and mitigating privacy risks.
AI-enhanced data masking
Synthesized utilizes AI-enhanced data masking techniques to anonymize and protect sensitive customer data, safeguarding privacy while maintaining data utility for development and testing purposes.
See documentation
