Data analysis is the systematic process of inspecting, cleaning, transforming, and modeling data to discover useful information and support decision-making. It encompasses exploratory data analysis (EDA), data cleaning, wrangling, and feature engineering—the critical preparatory steps that transform raw data into analysis-ready datasets. While often associated with statistics and machine learning, data analysis fundamentally serves as the bridge between raw observations and actionable insights. A key insight: spending adequate time on quality data preparation typically has a larger impact on model performance than algorithm selection itself—well-prepared data enables simpler models to outperform complex ones trained on poor data.