//! Data quality variations for realistic synthetic data.
//!
//! This module provides tools to introduce realistic data quality issues:
//! - Missing values (configurable by field)
//! - Format variations (dates, amounts, identifiers)
//! - Duplicates (exact and near-duplicates)
//! - Typos (substitution, transposition, insertion, deletion)
//! - Encoding issues (character corruption)
//! - Labels for ML training
//!
//! These variations make synthetic data more realistic for testing
//! data cleaning, ETL pipelines, and data quality tools.
pub use *;
pub use *;
pub use *;
pub use *;
pub use *;
pub use *;