Synthetic Data for Test Data
Generate representative Synthetic Test Data for non-production environments to deliver and release state-of-the-art software solutions
Introduction to test data
Organizations have non-production environments to safely develop and test software solutions without affecting the live or production system. Representative test data is important in these environments to accurately mimic real-world conditions and ensure that the software behaves as expected in production, helping to identify and fix issues early in the development process.
Testing with personal data is not allowed
Using production data as test data seems obvious, but using real personal data as test data is not allowed due to (privacy) regulations, such as the GDPR and privacy authorities, such as the Dutch Data Protection Authority. This introduces challenges for many organizations in getting the test data right. However, as solution, the Dutch DPA suggest using synthetic data or mock data as test data
‘’Testing with personal data is difficult to reconcile with the GDPR’’
‘’You can explore the availability of synthetic data or mock data’’
Test Data Challenges
- Business logic is not preserved and data does not reflect production data
- No referential integrity and consistency over datasets / databases / systems
Test data takes time and manual work
- Many manual configurations are needed from your developers
- Unstable self-build solutions introduce continuation risks
Test data does not cover new scenarios
- Production data does not cover for hypothetical future scenario’s
- For new functionalities, you do not have data at all
Our solution: Test Data Management
Utilize our best-practice solutions to generate test data that reflects production data for comprehensive testing and development in representative scenarios.
Create synthetic data based on pre-defined rules and constraints, aiming to mimic real-world data or simulate specific scenarios.
Reduce records to create a smaller, representative subset of a relational database while maintaining referential integrity
Do you have any questions?
Talk to one of our experts
Why do organizations use our Test Data Management Solutions?
Privacy-by-design and Production-like data
- Production-like synthetic test data generated based on your production data by the power of AI
- Preserved referential integrity for consistency over datasets / databases / systems
Easy, fast and agile
- Seamlessly refresh of your entire test environment
- Replace and minimzie manual work with AI
- Make your test data manageable
Test Data coverage for hypothetical scenarios
- Cover any hypothetical future scenario
- Full flexibility with rule bases generated synthetic data
- Create synthetic data from scratch, in case you do not have data (yet)
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Value
Deliver software solutions easier, faster, and with higher quality with representative synthetic test data
- Release faster and shorten the time-to-market
- Spot bugs faster and earlier in the development and testing cycle
- First-time-right deployments
- Improve overall test, development and delivery quality
- Utilize test and development resources smarter
- Higher NPS Scores
Save your synthetic data guide now!
- What is synthetic data?
- Why do organizations use it?
- Value adding synthetic data client cases
- How to start
