This case study analyzes Fitbit data to understand user engagement patterns through daily activity, sleep behavior, and step tracking. Using R and tidyverse tools, the analysis explores temporal patterns in activity, sleep, and segments users based on their consistency in tracking sleep and steps. The findings offer actionable insights for Bellabeat's marketing and product strategy, helping to tailor engagement approaches to different user profiles.

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The goal of this study was to analyze the Storm Events data provided by National Climatic Data Center. I initiated these analyses to address two specific questions to support decision making on resource planning for future: 1) Across the United States, which types of events are most harmful with respect to population health? 2) Across the United States, which types of events have the greatest economic consequences? This report describes the summary of results in a graphical format. Flood causes maximum number of fatalities followed by hail and excessive leading to total fatalities greater than 2000. In addition, flood events also cause highest economic losses.