A powerful and interactive Power BI dashboard to analyze Uber trip data and extract actionable insights for improved decision-making, resource optimization, and operational efficiency.
The Uber RideMetrics Suite is a comprehensive Power BI solution built to analyze Uber trip records and visualize key performance indicators (KPIs) across time, geography, and vehicle types.
This project empowers stakeholders to monitor ride trends, revenue generation, and trip efficiency with dynamic, interactive dashboards.
- Track and visualize key Uber trip metrics like Total Bookings, Total Booking Value, and Trip Distance
- Identify high-demand time periods and locations for operational planning
- Enhance data exploration using interactive charts, slicers, and drill-through functionality
- Optimize pricing and resource allocation using trend analysis and vehicle preference data
- KPIs: Total Bookings, Booking Value, Trip Distance, Avg Booking Value & Duration
- Charts: Measure Selector with dynamic visual updates by:
- Payment Type (Card, Cash, Wallet)
- Trip Type (Day/Night)
- Vehicle Type Analysis: Grid View with conditional formatting
- Location Metrics:
- Most Frequent Pickup & Drop-Off Points
- Farthest Trips
- Top 5 Booking Locations
- Preferred Vehicle per Location
- UX Enhancements:
- Dynamic Chart Titles
- Slicers (Date, City)
- Tooltips for deeper metric insight
- Dynamic Measure Filter β Filters all charts via user-selected KPIs
- Visuals:
- Area Chart by Pickup Time (10-min intervals)
- Line Chart by Day Name
- Heatmap (Matrix) β Hour vs. Day demand pattern
- Drill-through Functionality:
- View granular trip records from any visual
- Bookmark Toggle:
- Switch between filtered view and full dataset
- Power BI Desktop
- Power Query
- DAX (Data Analysis Expressions)
- Excel (Data Source)
Uber RideMetrics Suite.pbix
β Power BI dashboard fileUber Trip Details.xlsx
β Raw trip dataLocation Table.xlsx
β Supplementary location infoProblem Statement.docx
β Business requirement document
- Make informed decisions using data-driven insights
- Discover hidden patterns in trip distance, timing, and vehicle usage
- Support strategic planning through location and time-based analysis
- Enhance customer satisfaction and pricing strategies
- Add forecasting features using time-series models
- Integrate real-time data streaming with Azure or Databricks
- Embed dashboard into a web application for broader accessibility
Arunbaha Pani
(B.Tech CSE, UIT-RGPV Bhopal)