DATPROF is renowned for capabilities including collaboration without heavy supplier reliance, synthetic data generation, and data masking across applications. Its features allow flexible customization, integration with systems, and scalable masking. Users benefit from its intuitive design and efficient data management while seeking improvements in orchestration features, enhancing discovery-to-masking integration, and expanding APIs. Addressing requirements like template reusability, empty database functionality, and mainframe platform compatibility are focus areas. Suggestions for better synthetic data generation and mainframe alliances highlight future growth potential.
What are DATPROF's most valuable features?
- Subsetting for creating tailored data sets.
- User-friendly design aiding ease of use.
- Intelligent data modeling for efficient handling.
- Anonymization ensuring data privacy.
- Integration with different systems for broader applicability.
Which benefits should users consider?
- Reduced data storage costs through efficient subsetting.
- Compliance with regulations like GDPR via effective masking.
- Enhanced data management efficiency boosting team productivity.
- Improved data protection across database formats.
In industries requiring stringent data protection such as finance and healthcare, DATPROF is crucial for managing test databases, meeting CI/CD targets, and ensuring GDPR compliance. Teams leverage DATPROF for transitioning to cloud environments, masking sensitive data, and creating synthetic data, thereby supporting diverse IT environments.
DATPROF was previously known as DATPROF Privacy, DATPROF Test Data Management.