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Customer segmentation, sales trends, and supplier insights using SQLite + Power BI based on the Northwind dataset.

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techwithhams/Northwind-Sales-Analysis

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📦 Northwind Sales Analysis Project

End-to-End Portfolio Project | SQLite + Power BI

This project delivers a comprehensive analysis of the Northwind dataset, simulating a trading company. It highlights customer behavior, order patterns, product sales, employee performance, and supplier dynamics using structured SQL queries and Power BI dashboards.


🌟 Project Objective

To uncover actionable insights that improve customer segmentation, product strategy, supplier relationships, and employee performance in a B2B trading environment.


🧰 Tools & Skills

  • 📃 Dataset: Northwind Traders — SQLite relational database
  • 🧠 Analysis: Advanced SQL (joins, CTEs, aggregations, views)
  • 📊 Visualization: Power BI dashboards with dynamic KPIs, filters, drilldowns
  • 🛠 Tools Used: SQLite, Power BI
  • 🔍 Skills Applied: SQL, RFM segmentation, data modeling, DAX, dashboard design

📁 Project Structure

Northwind-Sales-Project/
│
├── Northwind_Sales_Script.sql              # Full SQL analysis script
├── Northwind_Sales_Dashboard.pdf           # Final Power BI dashboard
├── PowerBI_Screenshots/                    # Dashboard visuals by page
│   ├── 1. Sales Trends & Order Behavior.jpg
│   ├── 2. Customer Analysis & Segmentation.jpg
│   ├── 3. Product Analysis.jpg
│   └── 4. Supplier & Employee Insights.jpg
└── README.md                               # Project overview and documentation

🧠 Key Insights

👥 Customer Segmentation

  • RFM Segmentation revealed:

    • Champions: 6.45%
    • Potential Loyalists: 74.19%
    • At Risk: 19.35%
  • 60 customers classified as “Very Recent”

  • Most customers have medium frequency and order value

  • High-value customers tend to place large bulk orders

📦 Product Performance

  • 🏆 Top Revenue Products:

    • Côte de Blaye: $53.2M
    • Thüringer Rostbratwurst, Mishi Kobe Niku
  • 92% of revenue comes from high-priced items

  • Least sold products include: Röd Kaviar, Chef Anton's Cajun Seasoning

  • Bundling frequently co-purchased items can boost cross-sell potential

📅 Order Patterns

  • 📆 Top Months: August ($41.5M), July, March

  • 🕛 Most Active Hour: Midnight

  • 🗓️ Busiest Day: Monday | Slowest: Thursday

  • 📦 Order Size:

    • Bulk orders account for 74% of revenue

👩‍💼 Employee Performance

  • Margaret Peacock processed the most orders and generated the most revenue ($51.5M)
  • Michael Suyama had the highest AOV ($742)
  • UK-based employees drove 44% of total revenue despite being fewer than US-based ones

🚚 Supplier Insights

  • Top supplier countries by revenue:

    • 🇫🇷 France ($77.6M)
    • 🇩🇪 Germany ($68M)
    • 🇦🇺 Australia ($54.5M)
  • 10 most expensive products alone generated > $176M

  • Supplier performance varied across regions


📊 Power BI Dashboard

The report contains 4 interactive pages:

  1. Sales Trends & Order Behavior
  2. Customer Analysis & Segmentation
  3. Product Analysis
  4. Supplier & Employee Insights

📸 Preview screenshots available in the PowerBI_Screenshots folder. 📄 Dashboard PDF


💡 Business Recommendations

  • 🧲 Focus marketing on Champions and Potential Loyalists
  • 📦 Promote top-performing products and bundle frequent pairs
  • 📅 Align promotions with peak months like August and July
  • 👥 Recognize top employees and balance team workloads
  • 🌍 Optimize suppliers by performance and reconsider underperforming regions

📋 How to Use

  1. Load the Northwind SQLite database into any SQL editor.
  2. Execute Northwind_Sales_Script.sql to generate views and insights.
  3. Connect your Power BI report to the database or use the provided PDF.
  4. Explore the dashboard for performance breakdowns and segment trends.

📬 Author: Hams Saeed Alhakim 🔗 GitHub: github.com/techwithhams 🗓 Date: 2025