Smart De-Identification
Protect sensitive information by removing or modifying personally identifiable information (PII)
Introduction De-Identification
What is 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.
Why do organizations use De-Identification?
Numerous organizations handle sensitive information and accordingly, require protection. The objective is to enhance privacy, mitigating the risk of direct or indirect identification of individuals. De-identification is frequently utilized in scenarios necessitating data use, such as for testing and development purposes, with focus on preserving privacy and adhering to data protection regulations.
What makes Syntho’s solution smart?
Syntho utilizes the power of AI to allow you to de-identify smart! In our de-identification approach, we employ smart solutions on three fundamental elements. Firstly, efficiency is prioritized through the use of our PII Scanner, saving time and minimizing manual effort. Secondly, we ensure that referential integrity is preserved by applying consistent mapping. Lastly, adaptability is achieved through the utilization of our Mockers.
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.
What are typical use cases for de-identification?
De-identification entails the modification or removal of personally identifiable information (PII) from existing datasets and/or databases. It is particularly effective for use cases involving multiple relational tables, databases and/or systems and is commonly applied in test data use cases.
Test data for non-production environments
Deliver and release state-of-the-art software solutions faster and with higher quality with representative test data.
Demo data
Astonish your prospects with next-level product demos, tailored with representative data.
How can I utilize Syntho’s Smart De-Identification solutions?
Configure de-identification effortlessly within our platform with user-friendly options tailored to your needs. Whether you’re focusing on entire tables or specific columns within them, our platform provides seamless configuration capabilities.
For table-level de-identification, simply drag tables from your relational database into the de-identify section in the workspace.
Database-level de-identification
For database-level de-identification, simply drag tables from your relational database into the de-identify section in the workspace.
Column-level de-identification
To apply de-identification on a more granular level or column level, open a table, choose the specific column you want to de-identify, and effortlessly apply a mocker. Streamline your data protection process with our intuitive configuration features.
Save your synthetic data guide now!
- What is synthetic data?
- Why do organizations use it?
- Value adding synthetic data client cases
- How to start
