Bike Buyers Dashboard Project

Overview

This project involves the creation of a data analysis dashboard in Google Sheets to explore and visualize insights into the behavior and preferences of bike buyers. The dataset used for analysis contains details of 1000 users with various attributes such as marital status, gender, income, and whether or not they purchased a bike.

Project Steps

Step 1: Data Acquisition

Download the dataset provided or use a relevant dataset related to bike buyers, ensuring it includes customer demographics and purchase history.

Step 2: Google Sheets Set-up

Import the dataset into a new Google Sheets document, and familiarize yourself with basic functionalities like sorting, filtering, and basic formulas.

Step 3: Data Exploration

Explore the dataset to understand its structure and contents. Identify key variables that provide insights into bike buyers’ behavior and preferences.

Step 4: Dashboard Design

Plan the layout of the dashboard, deciding on key metrics and visualizations. Create sections for demographics, purchasing trends, and relevant categories.

Step 5: Data Analysis and Visualization

Utilize Google Sheets features to perform data analysis, create pivot tables, charts, and graphs. Visualize key metrics like customer age distribution, popular bike models, and purchasing patterns.

Step 6: Interactive Elements

Enhance the dashboard with interactive elements such as dropdown menus or filters, allowing users to dynamically explore the data.

Step 7: Insights and Recommendations

Draw insights from the analysis and use them to make informed recommendations. For example, identify popular bikes among specific age groups or demographics.

Step 8: Documentation

Document the steps taken to create the dashboard, explaining design choices and any challenges faced. Summarize the insights gained and recommendations made.

Files Included

• Bike_Buyers_Dataset.csv: The dataset used for analysis.

• Bike_Buyers_Complete.gsheet: Google Sheets document containing the dashboard (Inside drive link).

• Dataset_Info_(Bike Buyers): Contains all the necessary information and the tasks to be performed.

  Drive link here: https://docs.google.com/spreadsheets/d/10XH9eQqahFDVJWCJxqYpGiZUyMN8tttm47NLN7OwvD0/edit?usp=sharing

Dashboard Components

1. Demographics Section

   • Bar Chart: Marital Status
   • Bar Chart: Gender
   • Histogram: Income
   • Histogram: Age

2. Purchasing Trends Section

   • Box Plot: Income
   • Pie Chart: Region
   • Scatter Plot: Income vs. Age
   • Stacked Bar Chart: Marital Status & Gender

Usage

1. Open Bike_Buyers_Dataset.csv to access the raw dataset.
2. Open Bike_Buyers_Complete.gsheet from the given drive link, to view the dashboard and explore visualizations.

Contributing

If you'd like to contribute to the project, follow the standard GitHub workflow:

1. Fork the repository.
2. Create a new branch for your changes.
3. Make changes and commit them.
4. Submit a pull request.

Acknowledgments

Special thanks to PrepInsta for their collaboration and input throughout the project.

License

This project is licensed under the MIT License.

Note: This project was created as part of an internship by PrepInsta. All rights reserved by PrepInsta. For any inquiries regarding the use or distribution of this project, please contact PrepInsta.

Contact

For questions or feedback, contact Rupak Bera at [workwithrupak@gmail.com].

Enjoy exploring the insights into the fascinating world of bike buyers!