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📊 Customer Trend Analysis

Using Python, SQL & Power BI

🧾 Project Overview

This project focuses on analyzing customer shopping behavior to uncover meaningful business insights.
By combining Python, SQL, and Power BI, the project demonstrates a complete end-to-end data analytics workflow — from raw data processing to interactive dashboard reporting.

The goal is to help businesses understand:

  • Customer purchasing patterns
  • Product performance
  • Revenue trends
  • Customer retention behavior

and support data-driven decision making.


🧰 Tools & Technologies

  • Python – Data cleaning, preprocessing, and analysis
  • Pandas, NumPy, Matplotlib, Seaborn – Data manipulation & visualization
  • SQL – Querying and transforming data
  • Power BI – Interactive dashboards & business reporting

🔍 Key Analysis Performed

  • 🧮 Customer segmentation based on behavior
  • 📦 Product & category performance analysis
  • 🔁 Repeat purchase & retention analysis
  • 📈 Revenue and sales trend analysis
  • 🛒 Purchase frequency & order value insights

📊 Dashboard Insights (Power BI)

The Power BI dashboard presents:

  • Sales & revenue trends
  • Top-performing products & categories
  • Customer distribution & behavior
  • KPIs for business performance tracking

🧪 Project Workflow

  1. Data Collection
  2. Data Cleaning & Preprocessing (Python)
  3. Exploratory Data Analysis
  4. SQL-Based Query Analysis
  5. Dashboard Creation in Power BI
  6. Business Insight Generation

💡 Business Value

This project helps organizations:

  • Improve customer retention
  • Optimize product strategy
  • Identify growth opportunities
  • Enhance marketing decision making

📌 Conclusion

This project demonstrates strong skills in data analysis, visualization, and business intelligence, making it suitable for roles such as Data Analyst, Business Analyst, and Data Scientist.

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End-to-end customer trend analysis project using Python, SQL & Power BI for business intelligence and decision-making.

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