Skip to content
Back

Identity Disclosure Risk in a Fully Synthetic Dataset

Privacy preserving synthetic data

In today's digital age, data has become an integral part of every organization's operations. Companies gather and analyze vast amounts of data to make informed decisions and gain insights into their customers' behavior and preferences. However, the collection and processing of sensitive and personal information have raised concerns about privacy and security. This is where synthetic data comes in as a solution for data-sharing initiatives while ensuring privacy.

Synthetic data is artificially generated data that mimics real data patterns without duplicating the original dataset. It is generated through machine learning techniques that learn the statistical information from real data, enabling the creation of new, artificial data that is not linked to actual individuals or events. This data can be used in place of sensitive data for testing and development purposes, allowing for more secure and responsible data sharing.

In this use case, YData Fabric showcases the use of synthetic data for data-sharing initiatives and how to assess the risk of disclosure. YData Fabric's synthesizers use state-of-the-art machine learning techniques to generate synthetic data that reproduces the patterns and characteristics of the original data without compromising privacy.

 

Back
Differential privacy and privacy controls for synthetic data generation

Differential Privacy: Synthetic data privacy controls

In today's data-driven world, privacy concerns have become paramount. The use of personal data in various applications raises ethical and legal questions, prompting the need for privacy-preserving techniques. Differential privacy has...

Read More

YData Fabric Synthetic data vs SDV

Synthetic data is a cornerstone of Data Centric-AI, an approach that focuses primarily on data quality rather than models. For the past few years, synthetic data gained attention because of a wide range of applications such as data...

Read More
Synthetic Data resembles the creation of an artificial

Generative AI for Tabular Data

Data is the foundation of modern machine learning models. However, data privacy issues, high costs, and the difficulty in obtaining large datasets make it challenging to develop robust and efficient models. This is where synthetic data...

Read More