De-Identification & Synthetization
Comprehensive testing with representative data
Utilize our best-practice solutions to generate test data that reflects production data for comprehensive testing and development in representative scenarios.
Test Data Management
Create, maintain, and control representative test
data for non-production environments
Value of synthetic data
Explore how to use synthetic data in practise
Comprehensive
Testing Coverage
Create diverse datasets that cover wide ranges of scenarios, improving test accuracy and efficiency
Optimized Testing
and Development
Boost productivity and speed up development with adjustable data volumes for your test environments.
Production-Like
Test Data
Enhance testing accuracy by generating test data that closely replicates production environments.
Discover our features
Explore features to protect sensitive information and maintain data integrity.
Learn more
Rule-Based Synthetic Data
Simulate real-world scenarios
Create synthetic data based on pre-defined rules and constraints, aiming to mimic real-world data or simulate specific scenarios.
Subsetting
Create manageable data subsets
Reduce records to create a smaller, representative subset of a relational database while maintaining referential integrity.
Deploy Syntho
with your favorite tools
Syntho deploys within your secure environment, ensuring sensitive
data never leaves your premises. This allows data synthesis at the
source without external access.
Product Demo
Test Data Managemant
Use cases
Explore how synthetic data can be applied in real-life scenarios
Advanced Analytics
Build strong data foundations with easy and fast access to AI generated synthetic data
Fast Data Sharing
Explore how to eliminate data sharing challenges that you will face when sharing original data
Change to Pilots, Hackathons and Innovation
Fast prototyping and hypothesis validation before real data request performance
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What is synthetic data?
How does it work?
Why do organizations use it?
How to start?
Frequently Asked Questions
What is Test Data Management?
Test data management (TDM) is the process of creating, maintaining, and controlling the data used for non-production environments (test, development and acceptance environments).
Why do organizations use Test Data Management?
Production data is privacy-sensitive
Testing and development with representative test data is essential to deliver state-of-the-art software solutions. Using original production data seems obvious, but is not allowed due to (privacy) regulations according to the GDPR and the Dutch Data Protection Authority. This introduces challenges for many organizations in getting the test data right.
Production data does not cover all test scenarios
Test data management is essential because production data often lacks the diversity required for comprehensive testing (or does not (yet) exist at all), leaving out edge cases and potential future scenarios. By creating and managing diverse test data sets, it ensures thorough testing coverage and helps identify potential issues before deployment, mitigating risks and bugs in production to enhance software quality.
Optimize testing and development
Let your testers and developers focus on testing and development, instead of test data creation. Test data management optimizes testing and development by maintaining and updating test data, saving developers and testers time typically spent on data preparation. Automation of test data provisioning and refreshing ensures data relevance and accuracy, allowing teams to focus on analyzing results and enhancing software quality efficiently. This streamlined process improves overall testing speed, agility, and productivity in the development lifecycle.
Build better and faster with synthetic data today
Unlock data access, accelerate development, and enhance data privacy.
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