Utilize our best-practice solutions to generate test data that reflects production data for comprehensive testing and development in representative scenarios
Testing and development with representative test data is essential to deliver state-of-the-art solutions. Using original production data seems obvious, but is often challenging as it cannot simply be used because it:
This introduces challenges for many organizations in getting the test data right. Hence, Syntho supports all best practice solutions to establish your test data right.
Follow best practices to protect sensitive data while ensuring it remains useful for analysis and testing.
Identify PII automatically with our AI-powered PII Scanner
Mitigate manual work and utilize our PII scanner to identify columns in your database containing direct Personally Identifiable Information (PII) with the power of AI.
Substitute sensitive PII, PHI, and other identifiers
Substitute sensitive PII, PHI, and other identifiers with representative Synthetic Mock Data that follow business logic and patterns.
Preserve referential integrity in an entire relational data ecosystem
Preserve referential integrity with consistent mapping in an entire data ecosystem to match data across synthetic data jobs, databases, and systems.
Explore the Syntho user documentation
Create synthetic data based on pre-defined rules and constraints
Mimic statistical patterns of original data in synthetic data with the power of artificial intelligence
Scan PII automatically with our PII Scanner via the “PII” tab or identify columns that you would like to mock via the “Job Configuration” tab.
Confirm the by our PII scanner suggested mocker automatically or configure mockers on column level.
Confirm to apply the selected mocker to a column via the PII or Job Configuration tab. This allows users the flexibility to spot columns and apply mockers accordingly.
Mimic (sensitive) data with AI to generate synthetic data twins
Synthetic data for the National Statistical Office, Statistics Netherlands (CBS)
Empower CBS’s statistical excellence with secure synthetic data solutions and learn how they are shaping the future of statistical
Synthetic test and development data with a leading EMR and healthcare solutions
Case Study About the client The company specializes in developing and supporting a proprietary electronic medical record (EMR) software
Synthetic data for academic research at the Erasmus University
Revolutionize academic research at Erasmus University with synthetic data. Explore its power by reading our case study.
Synthetic data for the The Netherlands Chamber of Commerce (KVK)
Discover how synthetic data for a Dutch governmental organization enables fast, secure, and actionable initiatives.
Synthetic data for advanced analytics and testing with a leading international bank
Unlock the potential of synthetic data for AI/ML modeling, advanced analytics, and testing with a renowned International Dutch Bank.
Synthetic test and development data with a leading Dutch insurance company
Explore the innovative world of synthetic test and development data in collaboration with a prominent Dutch insurance company.
Synthetic data for software development and testing with a leading Dutch Bank
Check out how synthetic data for software development and testing can help solving privacy issues of a leading Dutch Bank.
Synthetic patient EHR data for advanced analytics with Erasmus MC
The company specializes in developing and supporting a proprietary electronic medical record (EMR) software application widely recognized
Synthetic data generation for data sharing with Lifelines
Are you curious how realistic are synthetic biobank data generation for data sharing? Learn more about it from our case study with a
Synthetic healthcare data for a leading US hospital
Are you curious how works synthetic healthcare data with a leading US hospital? Learn more about it from our case study
PII, PHI, and other direct identifiers are sensitive and can be spotted manually or automatically with our PII scanner to save time and minimize manual work. Then, one can apply Mockers to substitute real values with mock values to de-identify data and enhance privacy.
PII stands for Personal Identifiable Information. PHI stands for Personal Health Information and is an extended version of PII dedicated to health information. Both PII and PHI are identifiers and relate to any information that can be used to distinguish or trace an individual’s identity directly. Here, with identifiers, only one person shares this trait.
Test data management (TDM) is the process of creating, maintaining, and controlling the data used for non-production environments (test, development and acceptance environments).
Unlock data access, accelerate development, and enhance data privacy.
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