synthdata-tutorial

To generate synthetic data from a YAML schema, use a guided workflow that walks through template selection, data generation, extension, and anonymization. The tutorial provides structured steps to produce outputs from custom schemas without external tooling.

The synthetic data generation workflow covers generating, extracting, extending, anonymizing, and serving datasets. It guides users from schema creation through safe data anonymization to serving outputs via MCP for interactive querying.

Yes, you can serve synthetic datasets via MCP for interactive querying. The workflow includes a serve step that enables interactive access to the generated and anonymized data outputs.

No external tooling is required to anonymize real data. The workflow enforces safe usage through a structured, stepwise walkthrough using included scripts and references, requiring no dependencies beyond what is provided.

Yes, a hands-on tutorial is available for prototyping synthetic data pipelines. It is suitable for onboarding and quick-start experiments, guiding beginners through real-world templates and sample datasets in a scratch directory.

The best way to learn synthdata generation is through an interactive onboarding experience. The tutorial provides practical, stepwise guidance using real-world templates and custom schemas to build hands-on familiarity with core data skills.