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👨🏻‍💻 Customer Behavior Data Analyst Portfolio Project

This repository contains an end-to-end Data Analytics portfolio project developed by me to simulate real-world, industry-standard analytics workflows. The project demonstrates how raw customer data can be transformed into meaningful business insights using Python, SQL, and Power BI.

The objective of this project is to showcase my hands-on skills in data cleaning, analysis, visualization, and reporting, similar to the responsibilities of a professional Data Analyst in a business environment.

🎯 Project Objective

To analyze customer shopping behavior and uncover insights related to:

Purchase patterns

Discount impact

Customer demographics

Ratings and loyalty indicators

The project focuses on converting raw retail data into actionable business intelligence through structured analysis and visualization.

🧠 Skills & Tools Used

Python (Pandas, NumPy, Matplotlib, Seaborn)

SQL (PostgreSQL / MySQL)

Power BI (Interactive Dashboards)

Jupyter Notebook

Data Cleaning & Feature Engineering

Exploratory Data Analysis (EDA)

Business Insight Generation & Reporting

📌 Project Workflow

1️⃣ Data Preparation & EDA (Python)

Imported and explored the dataset

Handled missing values and data inconsistencies

Created new features (age groups, segments, etc.)

2️⃣ Data Analysis (SQL)

Loaded cleaned data into a relational database

Wrote analytical SQL queries to answer business questions

Analyzed customer segments, spending behavior, and discount effects

3️⃣ Visualization & Insights (Power BI)

Built an interactive dashboard

Visualized trends, KPIs, and customer behavior patterns

Enabled data-driven decision-making

4️⃣ Reporting & Presentation

Summarized insights and business recommendations

Prepared a structured project report and presentation

🛠️ How to Run This Project git clone https://github.com/your-username/customer_behaviour_analysis.git cd customer_behaviour_analysis

Open Customer_Shopping_Behavior_Analysis.ipynb

Run the notebook to explore, clean, and process the data

Load the processed data into SQL (PostgreSQL / MySQL)

Execute queries from customer_behavior_sql_queries.sql

Open customer_behavior_dashboard.pbix in Power BI

📊 Key Outcomes

Identified high-value customer segments

Analyzed the impact of discounts on purchase behavior

Discovered trends across age groups and product categories

Built a business-ready analytics dashboard

📜 License

MIT License — feel free to fork, star ⭐, or use this project for learning and portfolio purposes.

About

Customer Behaviour Analysis is a data analytics project that explores customer shopping patterns using SQL and Python. It focuses on data cleaning, feature engineering, and exploratory analysis to understand purchase behavior, discount impact, demographics, and ratings for business insights.

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