We use cookies to ensure that you have the best experience on our site.

What is Synthetic Data Generation?

Synthetic Data Generation is the process of creating artificial data that mimics real-world data distributions. It is used to protect privacy, improve AI training datasets, and test machine learning models in scenarios where real data is scarce or sensitive.

Data-informed decision-making
Data-informed decision-making balances data insights with human expertise and contextual knowledge. It integrates analytical findings with qualitative inputs to create a more comprehensive decision-making process.
Data analytics
Data analytics is the process of interpreting and examining data to extract insights and trends. It combines machine learning models and statistical methods to enhance decision-making, optimize performance, and detect anomalies.
Data masking
Data masking is a security technique that replaces real data with fictitious yet structurally similar data to prevent unauthorized access while maintaining usability. It is widely used in testing, analytics, and compliance processes to protect sensitive data such as personally identifiable information (PII) and financial records.