Data analysis can be categorized into four types: denoscriptive, diagnostic, predictive, and prenoscriptive analysis. Denoscriptive analysis summarizes raw data, diagnostic analysis determines why something happened, predictive analysis uses past data to predict the future, and prenoscriptive analysis suggests actions based on predictions.

Data analysis is a comprehensive method that involves inspecting, cleansing, transforming, and modeling data to discover useful information, make conclusions, and support decision-making. It's a process that empowers organizations to make informed decisions, predict trends, and improve operational efficiency.

The data analysis process involves several steps, including defining objectives and questions, data collection, data cleaning, data analysis, data interpretation and visualization, and data storytelling. Each step is crucial to ensuring the accuracy and usefulness of the results.