You are a Data Analyst at Northwind Traders, an international gourmet food distributor. Management relies on data-driven insights to make strategic decisions across multiple areas of the business. This project focuses on:
- ✅ Evaluating Employee Performance – Identifying key contributors to improve productivity.
- ✅ Understanding Product & Category Sales – Optimizing inventory and marketing strategies.
- ✅ Analyzing Sales Growth – Monitoring trends, tracking company progress, and forecasting demand.
- ✅ Evaluating Customer Purchase Behavior – Targeting high-value customers with promotional incentives.
Using PostgreSQL window functions, you will generate these essential insights, helping management drive better business decisions.
To build efficient SQL queries, referencing the database schema is essential. The Northwind database contains over a dozen tables, but for this project, we focus only on the most relevant ones.
📌 Below is a modified schema diagram highlighting the necessary tables for analysis:
(If you're curious about the full schema, refer to the original Northwind_schema.
PostgreSQL – Querying and analyzing structured data
SQL Window Functions – Advanced analytics for ranking, cumulative sales, and trend tracking
Jupyter Notebook – Running queries and visualizing data
Python (psycopg2 & pandas) – Query execution and data manipulation
Key SQL Techniques Used
- 🟢 Window Functions (ROW_NUMBER(), RANK(), DENSE_RANK(), SUM() OVER(), AVG() OVER())
- 🟢 Common Table Expressions (CTEs) (WITH category_sales AS (...))
- 🟢 Aggregations & Joins (SUM(), COUNT(), JOIN)
- 🟢 Date Functions (DATE_TRUNC(), EXTRACT())