This project was assigned during my Data Analyst Internship at Innobyte Services, where I honed my skills in:
- Data Preprocessing: Cleaning and transforming raw data into a structured format.
- Data Visualization: Creating meaningful dashboards to derive actionable insights.
This project focuses on analyzing Amazon Sales Data to uncover valuable business insights. With a cleaned dataset processed using Python and visualized through Tableau, the dashboard provides actionable insights into revenue, customer trends, geographical distribution, and category performance.
- Python: For data cleaning and preparation.
- Tableau: For dashboard creation and visualization.
To run this project, you need the following:
- Python 3.x
- Libraries:
pandas,numpy
- Libraries:
- Tableau Desktop (or Tableau Public for free access)
- Total Revenue, Orders, and Average Order Value.
- Best-performing states and cities.
- Sales distribution across Indian states/cities on an interactive map.
- Top-selling categories visualized with bar charts.
- Quantity sold by category/size.
- Revenue contribution by order status.
- Trends in revenue over time.
- Removed duplicates and null values.
- Standardized city names and product categories for consistency.
- Prepared the data for visualization using pandas.
- Interactive dashboard created to display key metrics and trends.
- Various chart types like bar charts, line charts, pie charts, and maps used for insights.
- Filters and slicers added for customized exploration of data.
Key Insights:
- Top categories: T-shirt and Shirts contributed to the highest revenue.
- Majority of revenue came from metros like Bangalore and Mumbai.
- Repeat customers contributed significantly to sales growth.