This capstone project focuses on sales analysis, customer segmentation, inventory trends, employee performance, and supplier ratings using Power BI and SQL. The dataset is sourced from the Northwind Traders database, a well-known sample database used for business intelligence and analytics.
The goal of this project is to provide data-driven insights that help businesses make informed decisions based on historical sales and customer behavior patterns.
The analysis covers multiple business aspects, including:
- Identify top-selling products and their contribution to overall revenue.
- Understand monthly and yearly sales trends to detect peak business periods.
- Determine sales distribution across different regions and categories.
- Classify customers based on their purchasing frequency and order value.
- Detect high-value customers (VIPs) to enhance customer retention strategies.
- Analyze customer buying behavior to improve marketing campaigns.
- Identify fast-moving and slow-moving products.
- Detect potential stockout scenarios and improve demand forecasting.
- Track inventory turnover rate to optimize stock management.
- Assess sales contributions of each employee in the organization.
- Identify top-performing employees based on total revenue generated.
- Compare employees' sales performance over time to measure consistency.
- Evaluate suppliers based on product availability and fulfillment rate.
- Identify suppliers with frequent delays or low-quality products.
- Implement a Radar Chart visualization to compare supplier performance.
This project leverages the following technologies for data analysis and visualization:
- Power BI: Used for creating interactive dashboards and data visualization.
- SQL: Used for extracting, transforming, and analyzing data from the database.
- DAX (Data Analysis Expressions): Utilized in Power BI for advanced calculations.
- Excel: Used for initial data validation and cleaning.
- 🚀 Top 5 Products: The highest-selling products contribute to X% of total sales.
- 📈 Sales Trends: Certain months show spikes in sales, helping businesses adjust stock accordingly.
- 🏅 Top Customers: Identified loyal and high-value customers, enabling personalized marketing strategies.
- 📦 Inventory Gaps: Found stock shortages in key product categories, suggesting better inventory planning.
- 🎯 Employee Performance: Determined that X employees drive most of the revenue, helping with performance-based incentives.
- ⭐ Supplier Ratings: Rated suppliers based on delivery time, product quality, and availability.
The repository is organized as follows:
📁 Northwind_Traders_Sales_Analysis
├── 📊 Power BI Reports (PBIX files)
├── 📜 SQL Queries for Data Extraction
├── 📑 Data Dictionary & Documentation
├── 📁 Raw Dataset
├── 📁 Processed Data
└── README.md (This file)
The dataset is sourced from the Northwind Traders database, which includes transactional sales data, customer information, order details, and product data. You can find the dataset here.
- Download the Power BI PBIX file from this repository.
- Load the dataset into Power BI or SQL Server.
- Explore the interactive dashboards to analyze business insights.
- Modify SQL queries or DAX calculations for custom analysis.
You can access and download the full project solution from Google Drive using the link below:
📌 Note: Ensure you have the necessary permissions to access the files.
🔹 Incorporate Machine Learning models for sales forecasting. 🔹 Automate data refresh using Power BI service and scheduled refreshes. 🔹 Enhance customer churn prediction based on past purchase behavior. 🔹 Add real-time data integration with APIs or cloud databases.
Hi! I’m Srideep Sarkar, a passionate Data Analyst & Data Scientist specializing in data visualization, business intelligence, and analytics. I have experience working with SQL, Power BI, and advanced data modeling techniques.
📌 Let’s Connect! 🔗 LinkedIn | 📧 Email
⚡ If you find this project useful, feel free to fork, star ⭐, or contribute! 🚀