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[In-Depth Guide] The Complete CTGAN + SDV Pipeline for High-Fidelity Synthetic Data

The article walks through a production‑grade synthetic data pipeline that combines CTGAN with the SDV ecosystem, starting from raw mixed‑type tables and ending with model serialization. It demonstrates how to attach metadata, enforce numeric and categorical constraints, and perform conditional sampling. The guide also evaluates synthetic output using SDMetrics diagnostic and quality reports as well as downstream classifier performance. By comparing AUC scores on real versus synthetic‑trained models, it proves the utility of the generated data for real‑world analytics.