DOI: https://doi.org/10.36347/sjet.2025.v13i01.005

Pages: 30-44

Exploratory Data Analysis (EDA) is a systematic approach to explore data through visualizations, statistical summaries, and identifying underlying patterns. It helps uncover data insights such as outliers, relationships within the dataset, and trends. EDA reveals information that influences the design and implementation of machine learning models. EDA insights provide a strong foundation for pipeline development and model deployment. Exploratory data analysis is generally the first step in any data analytics workflow. It allows analysts to detect dependencies and connections between factors. The results form a foundation for advanced activities like statistical analysis and help reduce potential failures by validating initial dataset assumptions.