This report presents an exploratory analysis of three large English text datasets (blogs, news, and Twitter) as part of a text prediction project. The goal is to prepare the data for building a predictive model that can suggest the next word based on user input. The analysis includes basic summaries, word distributions, and frequency visualizations. It also outlines the initial plan for developing a Shiny app using n-gram models.