This Power BI report analyzes bike rental patterns in Seoul, focusing on rental trends, weather influences, usage peaks, and demographic data. The report aims to provide insights for optimizing bike availability, improving customer satisfaction, and supporting urban mobility strategies in Seoul.
The dataset includes:
- Rental Data: Daily bike rental counts, rental locations, and times.
- Weather Conditions: Temperature, humidity, rainfall, and other weather factors.
- Holiday and Seasonal Data: Holiday effects and seasonal variations in rentals.
- User Demographics: Age groups and user types (casual vs. registered users).
- Rental Trends: Analyze daily, monthly, and seasonal rental patterns to identify peak usage times.
- Weather Impact Analysis: Correlate weather conditions (temperature, rain, humidity) with rental volumes.
- Holiday Influence: Assess how holidays and special events impact bike rental demand.
- Demographic Insights: Visualize user demographics to understand which groups are using the service most frequently.
- Location-based Analysis: Map of popular rental locations across Seoul to highlight demand hotspots.
This Power BI analysis delivers actionable insights into Seoul’s bike rental service, allowing stakeholders to optimize operations based on demand patterns, weather dependencies, and user demographics. It’s a valuable tool for urban planners and transportation departments in improving bike rental efficiency and accessibility.