Kubeflow

Synthetic data mimics real data's statistical properties and offers enhanced privacy, data availability, and reduced costs. Tools like Kubeflow Pipelines utilize open-source frameworks like SDV to generate synthetic data for varied applications. Evaluating synthetic data involves assessing its usability, fidelity, and privacy. The post highlights techniques and challenges in generating synthetic data and the role of on-premise and cloud environments in this process.

Synthetic Data Generation with Kubeflow Pipelines

Exploring the Creation and Usefulness of Synthetic Data

Using Synthetic Data Generators to Enable Multiple Environments without Data Transfer