Uber Taxi Trip Analysis Dashboard

Overview

This project involves creating an end-to-end Power BI dashboard to analyze Uber taxi ride data. The goal is to derive actionable insights and help stakeholders make data-driven decisions by visualizing key performance metrics such as total trips, fare, duration, and trip distribution.

Objectives

• Develop a user-friendly and interactive Power BI dashboard.
• Track and analyze metrics such as total trips, total fares, trip distribution by location and time, and night trip percentages.
• Provide insights into customer behavior, payment methods, and trip trends.

Key Features

1. KPIs Displayed:

   • Total Trips Count
   • Total Fare
   • Total Duration
   • Total Distance
   • Night Trip Percentage

2. Business Requirements:

   • Geographic Insights: Visualize trip distribution by location.
   • Time-Based Analysis: Analyze trip patterns by day and time.
   • Payment Breakdown: Show payment types used for trips.

3. Dashboard Elements:

   • Filters Panel: Allow filtering by month, day, and location.
   • Visualizations: Include bar charts, donut charts, line charts, and KPI cards.
   • Interactive Design: Enable dynamic visuals through slicers and field parameters.

Steps to Create the Dashboard

1. Understand the Data:

   • Two data sources: Trip Details Fact Table and Location Dimension Table.
   • Examine relationships and data types for accurate analysis.

2. Load Data:

   • Import Trip Details and Location Dimension tables into Power BI Desktop.

3. Data Transformation:

   • Clean and standardize data using Power Query.
   • Create new columns and replace inconsistent values.

4. Data Modeling:

   • Create a date table for time-based analysis.
   • Define relationships between fact and dimension tables.

5. DAX Calculations:

   • Write measures for KPIs like total trips, fare, duration, and distance.
   • Add calculated columns such as day/night trip classification.

6. Visualizations:

   • Use charts, maps, and KPI visuals to represent data.
   • Design a layout emphasizing clarity and accessibility.

7. Publish and Share:

   • Publish the report to Power BI Service and configure sharing settings.

Key Insights

• Trip Trends: Identify peak hours, locations, and travel patterns.
• Revenue Analysis: Determine revenue trends by date and location.
• Customer Preferences: Understand payment method distribution and night trip behavior.

Technology and Tools Used

• Power BI Desktop: Data modeling, visualization, and DAX calculations.
• Power Query: Data cleaning and transformation.
• DAX (Data Analysis Expressions): Advanced calculations for metrics.

How to Use

1. Clone this repository.
2. Open the .pbix file in Power BI Desktop.
3. Explore the dashboard and apply filters to analyze data dynamically.
4. Modify or enhance the visuals and measures as needed.

Conclusion

This project serves as a practical guide for building comprehensive dashboards in Power BI. It helps beginners understand the process of transforming raw data into valuable business insights through data visualization.

Feel free to fork this repository and adapt it to your specific project needs!