Smart De-Identification and Synthetization
Utilize our best-practice solutions to generate test data that reflects production data for comprehensive testing and development in representative scenarios
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Using original personal data
as test data is not allowed
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:
- contains (privacy) sensitive information,
- is limited, scarce or misses data
- or does not exist at all.
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.
Best practices for
representative test data
Follow best practices to protect sensitive data while ensuring it remains useful for analysis and testing.
Smart De-Identification
PII Scanner
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.
Synthetic Mock Data
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.
Consistent Mapping
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.
User documentation
Explore the Syntho user documentation
Synthetic Data Generation
Synthetic Mock Data
Substitute sensitive PII, PHI, and other identifiers
Rule Based
Synthetic Data
Create synthetic data based on pre-defined rules and constraints
AI Generated
Synthetic Data
Mimic statistical patterns of original data in synthetic data with the power of artificial intelligence
De-Identification and
Synthetization in 3 steps
Identify PII
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.
Select Mockers
Confirm the by our PII scanner suggested mocker automatically or configure mockers on column level.
Confirm Mocker
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.
Trusted by enterprise companies
Mimic (sensitive) data with AI to generate synthetic data twins
Frequently Asked Questions
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.
- First name
- Last name
- Phone number
- Social Security Number, SSN
- Bank number, etc.
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).
Build better and faster with synthetic data today
Unlock data access, accelerate development, and enhance data privacy.
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