Visual Summaries of analyses of event system logs are important for understanding human analysis behaviors and patterns. This project aims at exploring the use of impression logs and event logs of the users present in the MIND dataset to understand their behavior toward the news articles they come across in their day-to-day lives. MIND or MIcrosoft News Dataset is a large-scale dataset generated using click-logs for news recommendation research. The data at hand is useful in providing insights about the popularity of keywords, and news articles based on different criteria like - Title length, Abstract Length, Time segments, etc. The tools and technologies used for data engineering and manipulation, exploratory analysis, and generating dashboards containing visualization summaries and reports include Tableau, and pandas library. These insights can be used to broaden our understanding of how to generate interactive, and clickable headlines for news articles, and to aid journalists and news officials design better news for the users.