An end-to-end Data Analytics project on the Northwind Traders dataset — uncovering sales trends, customer segments, product performance, and shipping efficiency through SQL, Excel, and Power BI.
Northwind Traders is a fictional wholesale company. This project performs a full analytics pipeline — from raw SQL extraction to an interactive Power BI dashboard — to answer key business questions around revenue, customer behaviour, product performance, and logistics.
Scale: $1.27M total sales · 2,155 orders · 90 customers · 21 countries · 77 products · 9 employees
- Which products and categories drive the most revenue?
- Who are the highest-value customers, and where are they located?
- Which employees contribute the most to sales?
- Which shippers are most efficient, and where are delays happening?
| Tool | Purpose |
|---|---|
| SQL (PostgreSQL) | Data extraction & querying |
| Excel | EDA, pivot analysis & data cleaning |
| Power BI + DAX | Data modeling, KPIs & dashboard |
The Northwind dataset includes 6 core tables:
Customers · Orders · Order Details · Products · Employees · Shippers
SQL Extraction → Excel EDA & Cleaning → Power BI Modeling → DAX KPIs → Dashboard
- SQL — Queried and joined tables to extract relevant business data
- Excel — Exploratory analysis, pivot tables, and data validation (
EDA.xlsx) - Power BI — Built star-schema data model and interactive visuals (
Northwind_Traders.pbix) - DAX — Created calculated measures for revenue, growth rate, and rankings
- Reporting — Exported findings to PDF and PowerPoint
- Beverages is the top-grossing category at $268K (21.16%), followed by Dairy Products at $235K (18%)
- QUICK-Stop, Ernst Handel, and Save-a-lot Markets are the top 3 customers, contributing $110K, $105K, and $104K respectively
- 64.87% of orders are below $500 in value — indicating a large base of small-ticket transactions
- Federal Shipping is the fastest shipper at 7.4 avg days; United Package is slowest at 9.0 days despite handling 39% of orders
- Margaret is the top-performing employee with $0.23M in total sales — nearly 3x the lowest performer
- Overall on-time delivery rate is 95.54% across 830 shipped orders with $64.94K total freight cost
 📌 Overview |
 👥 Customers Analysis |
 🧑💼 Employee Analysis |
 📦 Product Analysis |
 🚚 Shipper Analysis |
 🏭 Supplier Analysis |
NorthWind_Traders_Analytics/
│
├── Images/ # Dashboard screenshots (6 pages)
├── EDA.xlsx # Exploratory Data Analysis in Excel
├── MECE.docx # Structured problem breakdown
├── Northwind_Traders.pbix # Power BI dashboard file
├── Northwind_Traders.pdf # Exported dashboard report
├── NORTHWIND-TRADERS-REPORT.pptx # Presentation slides
└── README.md
git clone https://github.com/Mayank230604/NorthWind_Traders_Analytics.git
cd NorthWind_Traders_Analytics- Open
Northwind_Traders.pbixin Power BI Desktop to explore the full interactive dashboard - Open
EDA.xlsxin Excel to review exploratory analysis and pivot tables - Open
NORTHWIND-TRADERS-REPORT.pptxfor a presentation summary of findings
- Identify top customers for targeted retention and upselling strategies
- Optimize inventory by focusing on high-revenue categories (Beverages, Dairy)
- Reduce logistics cost by renegotiating with slower, costlier shippers
- Use employee performance data to align incentives with top contributors
SQL Querying · Data Cleaning · Exploratory Data Analysis · Data Modeling · DAX · Power BI Dashboarding · Business Analysis · Storytelling with Data
Mayank Adeva — Aspiring Data Analyst
B.Sc. Computer Science, Ramanujan College, University of Delhi (2025)
Skilled in SQL · Python (pandas, numpy) · Power BI · Excel · Git
📫 Open to entry-level Data Analyst roles — feel free to connect!
