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.
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: Smart De-identification and synthetization
Smart De-Identification
What is Smart De-identification
De-identification is a process used to protect sensitive information by removing or modifying personally identifiable information (PII) from a dataset or database.
When to use Smart De-identification as test data?
De-identification is often used when production data is available as a starting point. De-identification is applied to remove or modify (privacy) sensitive information from the dataset or database to comply with data privacy regulations, as the use of personal data is not allowed according to privacy regulations (such as the GDPR).
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.
Synthetic Data Generation
What is data synthetisation?
Synthetisation aims to create synthetic data that is generated artificially and serves as an alternative to real-world data.
When to synthetization as test data?
Synthetisation is often used when production data is limited, scarce, misses data or does not exist at all as a starting point. New data is artificially generated and serves as an alternative to real-world data.
Substitute sensitive PII, PHI, and other identifiers
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
Check our User Documentation here
How can one use Smart De-identification and synthetic data with Syntho?
Configure easily!
From smart de-identification to synthetization, the Syntho Engine supports all best-practice solutions to get your test data right. Configure all best practice test data solutions effortlessly within our platform with user-friendly options tailored to your needs. From smart de-identification to synthetization, simply drag the target table into the desired section in the workspace. Combining solutions is also supported.
Other features from Syntho
Explore other features that we provide
Build better and faster with synthetic data
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