Sales Data Analysis and Dashboard Development

📌 Overview

The Sales Data Analysis and Dashboard Development project focuses on analyzing sales data to gain insights into business performance. The project includes SQL-based data processing, Power BI visualizations, and key performance metrics to support data-driven decision-making.

🛠️ Features

• Interactive Power BI dashboard for visualizing sales trends
• SQL-based data processing and transformation
• Key insights into sales performance, profitability, and revenue trends
• Data-driven decision-making through analytics

📂 Project Structure

Sales-Data-Analysis-and-Dashboard-Development/
│-- Sales-Data-Analysis.pbix          # Power BI report file
│-- Sales-key-insight.png             # Image of key insights from the dashboard
│-- sales-performance-insight.png     # Visual representation of sales performance
│-- sales-profit-analysis.png         # Profitability insights visualization
│-- db_dump_version_2.sql             # SQL database dump for sales data
│-- README.md                         # Project documentation

🚀 Installation & Setup

Prerequisites

Ensure you have the following tools installed:

• Microsoft Power BI Desktop – For viewing and modifying the dashboard
• SQL Database (MySQL/PostgreSQL/SQL Server) – To restore and query sales data

Steps to Run the Project

1. Restore the Database:

   • Use the provided db_dump_version_2.sql file to restore the sales database.
   • Example command for MySQL:

     mysql -u username -p database_name < db_dump_version_2.sql

2. Open the Power BI Report:

   • Load the Sales-Data-Analysis.pbix file in Microsoft Power BI Desktop.
   • Ensure database connections are properly configured.

📊 Key Insights

• Sales Trends: Identify monthly/quarterly/yearly sales variations.
• Profit Analysis: Compare revenue vs. cost to analyze profit margins.
• Performance Metrics: Understand high-performing products, regions, and customers.
• Visual Dashboards: Easily interpret data using graphs, charts, and tables.

🔍 Technologies Used

• SQL – Data extraction and transformation
• Power BI – Data visualization and interactive reporting
• Excel/CSV – Data preprocessing (if applicable)

📌 Future Improvements

• Automating data updates in the Power BI report
• Enhancing dashboard interactivity with advanced filtering options
• Integrating predictive analytics for forecasting sales trends

📜 License

This project is open-source and available under the MIT License.