What is the main objective of exploratory data analysis (EDA)?

The main objective of exploratory data analysis (EDA) is to summarize and analyze the characteristics of a dataset. EDA is a crucial step in the data analysis process where statistical and visual techniques are employed to understand the underlying patterns, distributions, and potential relationships within the data. This allows data analysts to generate insights, identify anomalies, and refine hypotheses before conducting more formal analyses.

By summarizing data characteristics, EDA also helps to identify trends, correlations, and outliers, which can inform further investigation or model development. This phase is foundational because it lays the groundwork for more sophisticated analyses, including predictive modeling. In contrast, objectives like structuring data, forecasting future trends, or optimizing storage techniques are related to different aspects of data management and analysis, rather than the primary aim of EDA itself.