This project involves end-to-end data analysis of a bike shop service, aimed at analyzing key performance metrics such as hourly revenue, profit and revenue trends, seasonal revenue, and rider demographics. The dataset provided includes information on trips, riders, and revenue data over a certain time period.
The project is structured as follows:
- Database Creation: The dataset is imported and stored in a database for data manipulation and analysis.
- Data Analysis: Various metrics and insights are derived from the dataset to understand the business performance.
- Power BI Integration: The database is connected to Power BI for visualization and dashboard creation.
- Dashboard Creation: A dashboard is developed using Power BI to present key metrics and visually analyze them.
To run the project, ensure you have the following dependencies installed:
- SQL
- Power BI Desktop
- Database Creation: a. Import the dataset into a database management system (e.g., SQL). b. Perform necessary data cleaning and preprocessing.
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Data Analysis: a. Use SQL queries or Python Pandas to analyze the data and derive insights. b. Calculate key performance metrics such as revenue, profit, rider demographics, etc.
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Power BI Integration: a. Connect the database to Power BI using appropriate drivers. b. Import the necessary tables for visualization.
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Dashboard Creation: a. Create visualizations and charts in Power BI to represent the key metrics. b. Build a dashboard that provides an overview of the ride-hailing service's performance.
This project is licensed under the MIT License.