This document presents a concise exploratory analysis of the en_US.twitter.txt dataset from the SwiftKey corpus. It includes key summary statistics such as line counts, word totals, and average words per tweet. Through visualizations like histograms and word clouds, the report highlights frequent terms and patterns in user-generated content. A frequency table of top words complements the visuals, and a brief narrative explains the linguistic trends observed in the sample. The report is written in a clear, manager-friendly style to support decision-making and project planning. It confirms that the data has been successfully loaded and understood, and outlines next steps for building a predictive text model and deploying a Shiny app.

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Taking a closer look at potential patterns behind flights that were either canceled or excessively delayed.