📊 Sales Revenue Optimization Project

Full-stack business analytics project using SQL, Python (Pandas + Matplotlib), and Power BI.

🚀 Project Overview

This project focuses on analyzing retail sales performance and building an end-to-end Sales Revenue Optimization Dashboard. It answers key business questions such as:

Which categories drive the highest sales?

Which regions are most profitable?

What sub-categories underperform?

What is the monthly sales trend?

How can business decisions be improved using data?

🧰 Tech Stack 🔹 SQL (MySQL)

Data cleaning

Data profiling

KPI calculation

Generating business insights

🔹 Python (Pandas + Matplotlib)

Data loading & cleaning

Exploratory Data Analysis (EDA)

Matplotlib visualizations for trends & distribution

🔹 Power BI

KPI cards

Bar charts & line charts

Region-wise profitability

Slicers (Year, Category, Region)

Interactive Sales Revenue Optimization Dashboard

📁 Folder Structure Sales_Revenue_Optimization/ │ ├── Data/ │ └── Sample - Superstore.csv │ ├── SQL/ │ ├── 01_setup.sql │ ├── 02_data_cleaning.sql │ ├── 03_kpi_queries.sql │ └── 04_business_insights.sql │ ├── Notebooks/ │ └── superstore_eda.ipynb │ ├── Dashboard/ │ └── Sales_Revenue_Optimization.pbix │ ├── Project_Report.Screenshot │
│ └── README.md

📌 Key KPIs Generated KPI Description Total Sales Overall revenue Total Profit Profit generated Total Orders Number of unique orders Total Products Unique product count Total Customers Unique customers 📈 Python EDA Highlights

Using Pandas + Matplotlib:

✔ Most popular categories ✔ Highest revenue sub-categories ✔ Monthly sales trend ✔ Distribution of discount, quantity, profit

📊 Power BI Dashboard Features

✔ Interactive slicers (Category, Region, Segment, Year) ✔ Total Sales, Profit, Orders displayed cleanly ✔ Category-wise sales bar chart ✔ Region-wise profit bar chart ✔ Monthly sales trend line chart ✔ Sub-category performance chart ✔ Professional UI styling (theme, shadows, frames)

🔍 Business Insights (SQL + Python + BI)

Technology is the highest revenue-generating category

West region contributes the highest profit

Binders, Phones, Chairs dominate sub-category sales

December shows the strongest seasonal sales spike

Some sub-categories like Fasteners & Labels underperform

🧾 How to Run the Project 1️⃣ SQL

Import the SQL files in this order:

01_setup.sql

02_data_cleaning.sql

03_kpi_queries.sql

04_business_insights.sql

2️⃣ Python Notebook

Run:

superstore_eda.ipynb

3️⃣ Power BI

Open:

Sales_Revenue_Optimization.pbix

📬 Contact

Akshat Singh Aspiring Data Analyst | SQL • Python • Power BI www.linkedin.com/in/akshatsingh03