This project explores the Northwind Traders dataset, a widely used simulated business database provided by Microsoft. It represents a fictional company that imports and exports a variety of food products globally.
The primary goal is to extract actionable insights to guide decision-making in areas such as customer behavior, sales performance, shipping efficiency, and employee productivity. By analyzing relationships within the dataset, trends and opportunities for improvement have been identified.
The dataset encompasses multiple aspects of business operations, including customer orders, product details, employee activities, and shipping logistics. Key objectives of this project include deriving insights to help teams optimize processes and improve overall efficiency.
- Customers: Client details, including locations and contact information.
- Products: Information on goods sold, such as categories and prices.
- Categories: Classification of products into distinct groups.
- Employees: Roles, activities, and reporting structure.
- Orders & Order Details: Sales transactions and the products involved.
- Shippers: Details of companies managing order fulfillment.
The following diagram illustrates the structure and relationships between the tables in the dataset. It serves as a roadmap for understanding how the data is interconnected.
- PostgreSQL : For data extraction, transformation, and analysis.
- Python: For advanced analysis and visualization using libraries like pandas, matplotlib, and seaborn.
- Power BI: To create interactive, dynamic dashboards summarizing key insights for different departments.
- Sales Performance Analysis: Seasonal trends, regional sales patterns, and top-performing product categories were analyzed to optimize sales strategies.
- Customer Segmentation: Customer purchasing behavior was examined to group them into segments, enabling more targeted marketing and personalized engagement.
- Product Profitability: Product performance was evaluated, taking into account sales volume, discounts, and return rates to identify high-margin products and optimize pricing.
- Shipping Efficiency: Shipping costs and delivery delays were assessed to streamline logistics and enhance operational efficiency.
- Employee Productivity: Employee contributions and performance metrics were measured to identify areas for improvement and enhance overall productivity.
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