The Ola Dashboard project is an interactive data visualization tool designed to analyze and derive insights from ride-hailing data. Built using SQL, Excel, and Power BI, this project showcases essential metrics and trends in the Ola ecosystem, offering stakeholders actionable insights to enhance decision-making.
🚀 Overall Performance: Summarizes key KPIs such as total rides, revenue, average ratings, and cancellation rates.
🚖 Vehicle Type Analysis: Provides detailed insights into ride distribution and performance across vehicle categories.
💰 Revenue Trends: Highlights revenue patterns over time, broken down by regions and vehicle types.
❌ Cancellations: Identifies common cancellation reasons and their frequency to help improve customer experience.
⭐ Customer Ratings: Analyzes ratings trends to ensure service quality and user satisfaction.
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SQL: Extracted, cleaned, and transformed raw data for analysis.
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Excel: Used for initial data wrangling, aggregation, and quick pivot-based insights.
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Power BI: Created interactive dashboards with slicers, dynamic visuals, and customized layouts.
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This project provided valuable insights into:
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High-performing vehicle types and regions.
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Seasonal and temporal revenue trends.
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Areas for operational improvement, such as reducing cancellation rates.
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Opportunities to enhance customer satisfaction based on ratings and feedback.
🚧 Challenges and Solutions
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Data Integration: Unified multiple datasets using SQL joins and transformations.
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Visualization Performance: Optimized Power BI reports for faster load times and smoother interaction.
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Dynamic Filtering: Implemented slicers and filters in Power BI to allow users to explore specific scenarios.
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Predictive Analytics: Integrate forecasting models to predict demand and revenue trends.
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Customer Segmentation: Add segmentation features to tailor insights for different user groups.
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Geospatial Analysis: Enhance maps for more granular location-based insights.