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📊 INVENTORY OPTIMIZATION FOR RETAIL-sql-analysis

This project is an end-to-end SQL analysis of a retail business using real-world datasets. It showcases practical SQL skills applied to demand forecasting, pricing optimization, inventory management, and performance evaluation.


📂 Project Structure

sql-retail-analysis
├── datasets/
│   ├── demand_forecasting.csv
│   ├── inventory_monitoring.csv
│   ├── manager_details.csv
│   ├── pricing_optimization.csv
│   └── product_master.csv
├── sql_queries.sql         -- Full set of 25 optimized SQL queries
├── insights_summary.md     -- Business-ready insights and use cases
└── README.md               -- Project overview and explanation

📊 Key Analytical Objectives

  • Analyze demand, revenue, seasonality, and sales patterns
  • Identify low-stock, high-demand product risks
  • Compare pricing against competitors
  • Assess store and manager performance
  • Evaluate warehouse utilization efficiency
  • Analyze customer segments for revenue contribution

🧠 Insights Extracted

  • 💰 Total sales quantity & revenue
  • 🌦️ Seasonality-driven demand trends
  • 🏆 Top 10 best-performing products
  • ⚠️ Products at risk of stockouts
  • 🧾 Pricing vs discounts vs competitors
  • 🔁 High return-rate product flags
  • 👥 Revenue distribution by customer segment
  • 🏬 Warehouse space utilization
  • 👨‍💼 Manager & store location performance

👉 View the full insights in insights_summary.md


🛠️ Tools Used

  • Data Cleaning & Loading: Python
  • Database: MySQL
  • Language: SQL
  • Data Source: CSV files (Kaggle-style format)
  • Platform: GitHub

🚀 How to Run This Project

  1. Clone the repository
  2. Import the CSV files into your MySQL environment
  3. Run the queries from sql_queries.sql
  4. Review insights and apply for business decision-making

📎 Datasets Overview

File Description
demand_forecasting.csv Sales, price, promo, customer data
inventory_monitoring.csv Stock levels, lead time, reorder points
manager_details.csv Manager and store location mapping
pricing_optimization.csv Price, discounts, return rate, reviews
product_master.csv Category and subcategory per product

🌟 About Me

Hi, I’m Meshva Patel

A Data Analyst and aspiring Data Scientist with a passion for uncovering stories hidden in data. My journey is all about exploring how data shapes strategy, and each project helps me grow closer to that goal.

Feel free to connect with me on LinkedIn or explore more of my work on GitHub, or reach out via email at meshvapatel.ds@gmail.com.


📌 Tags

#SQL #DataAnalytics #RetailAnalysis #PortfolioProject #MySQL #BusinessInsights

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An end-to-end SQL data analysis project using retail datasets to extract business insights.

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