Product Sales Analysis
This project leverages data analytics to reveal patterns and insights hidden in product sales datasets. Its aim id to extract valuable insights to enhance strategic decision-making.
Achieved Goals :
The project focuses on analyzing sales data to identify trends, top-selling products, and revenue metrics for business decision-making. The following goals were achieved:
- Identify the best-selling products based on sales.
- Identify the top five cities with the highest sales. - Determine how much profit was made. - Identify the day of the week and the month with major sales.
My steps to complete this project :
To complete this project, the following steps were performed:
- Data acquisition and preparation.
- Data cleaning and transformation in Power Query.
- Data analysis and visualization in Power BI Desktop.
- Data Interpretation to uncover insights.
- Provide recommendations to enhance sales strategies and optimize sales performance.
Required Tools for this project :
The following tools were used:
- Power Query in Power BI to clean the data.
- Power BI to analyze the data and build the dashboard.
Conclusion :
This project analyzed sales data to identify trends, top-selling products, and revenue metrics for business decision-making. Some key findings:
- December was identified as the month with major sales. On the contrary, January was the month with lower sales, followed by February. - The top five cities with the most sales were Los Angeles, San Francisco, Atlanta, New York City, and Boston. - Developing marketing campaigns and promotions focused on best-selling products could boost sales and capitalize on their popularity. - Collecting and analyzing customer feedback could help identify pain points and areas for improvement.
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