What type of analytics questions include exploratory data analysis?

Exploratory data analysis (EDA) primarily falls under descriptive analytics because it focuses on summarizing and visualizing the main characteristics of a dataset. The goal of EDA is to explore the data, detect patterns, spot anomalies, and test hypotheses, primarily through visual methods and summary statistics without making any formal predictions or decisions.

Descriptive analytics provides insights into what has happened in the past and helps in understanding the underlying structure of the data. Through techniques such as plotting data, calculating averages, and examining distributions, descriptive analytics provides a foundation for further analysis and is essential in guiding the next steps in data exploration or modeling.

In contrast, prescriptive analytics aims to provide recommendations on actions to take, predictive analytics focuses on predicting future events based on historical data, and diagnostic analytics tries to explain why something happened. These approaches are vital in their own right, but they do not encompass the foundational exploratory activities that define exploratory data analysis.