Tabular data is data organized in rows and columns, like a spreadsheet or database table, where each row represents an observation and each column a feature. It is the most common data format in business: sales records, customer databases, financial transactions, and HR systems all produce tabular data. Traditional ML algorithms (random forests, XGBoost, gradient boosting) often outperform deep learning on tabular data, making feature engineering and model selection especially important.