Exploratory Data Analysis (EDA) and Purposeful EDA

Welcome to the Fourth Track, titled "Exploratory Data Analysis (EDA) and Purposeful EDA". In this track, you will explore the seven key steps of exploratory data analysis, starting from understanding user needs to performing analysis. This includes a detailed look into profiling, ideating, translating questions, collecting data, curating, transforming, and analyzing insights.  The track also covers essential EDA patterns: Comparison, Distribution, Relationship, and Composition. You will learn techniques for comparing entities, understanding data distribution through quartiles and box plots, analyzing variable relationships with scatter plots and correlation, and measuring parts of a whole. Additionally, you will learn to utilize advanced EDA tools for impactful insights and business problem-solving.