👨🏻‍💻Customer Behavior Data Analyst Portfolio Project

This project represents a complete, industry standard, end-to-end data analytics workflow, designed to mirror the real responsibilities of professional analysts in modern business environments. The project encompasses all critical stages of data analysis, from data preparation and modeling to insight generation, visualization, and reporting.

This project is perfect for:

• 📊 Data Analyst aspirants who want to build a strong Portfolio Project for interviews and LinkedIn
• 📚 Anyone learning Python, SQL, and Power BI
• 💼 Professionals preparing for interviews in Data Analytics, Data Science or Product Analytics roles

📌 Project Overview

The goal of this project is to simulate a corporate-grade end-to-end data analytics workflow, demonstrating the ability to translate raw data into strategic business intelligence by:

✅ Data Preparation,Modeling & Exploratory Data Analysis (Python): Clean and transform the raw dataset for analysis.

✅ Data Analysis (SQL): Simulate business transactions, and run queries to extract insights on customer segments, loyalty, and purchase drivers.

✅ Visualization & Insights (Power BI): Build an interactive dashboard that highlights key patterns and trends, enabling stakeholders to make data-driven decisions.

✅ Report and Presentation: Write a clear project report summarizing your key findings and business recommendations. Prepare a presentation that visually communicates insights and actionable recommendations to stakeholders.

🛠️ How to Use This Project

1. Clone the repository

   git clone https://github.com/sumitkurunkar512/Customer-Trends-Data-Analysis-SQL-Python-Power_BI/tree/main/customer-trends-data-analysis-SQL-Python-PowerBI-main
   cd customer-trends-data-analysis-SQL-Python-PowerBI

2. Open Customer_Shopping_Behavior_Analysis.ipynb notebook

   This file contains:

   • Data Import

   • Data exploration

   • Data cleaning

   • Connection to SQL Database

3. Load the data from Python notebook into MySQL/PostgreSQL/MS SQL Server

   • Create a database in SQL

   • Run Python code to load data into SQL database

   • Open customer_behavior_sql_queries.sql

   • Answer Business Questions using SQL Queries

4. Connect the SQL Database to Power BI

   • Open customer_behavior_dashboard.pbix

   • Create interactive dashboard in Power BI

5. Create Project Report and Presentation

   • Create project report

   • Build presentation deck using Gamma AI

6. Follow along with the YouTube video for full walkthrough. 👨‍💼

📜 License

MIT — feel free to fork, star, and use in your portfolio.

👨‍💻 About the Author

Hey, I’m Sumit Sachin Kurunakar, a Data Analyst. I break down complex data topics into simple, practical content that actually helps you land a job.

💼 LinkedIn: SUMIT KURUNKAR

• Let’s connect professionally and grow your data career

💡 Thanks for checking out the project! Your support means a lot! Feel free to star ⭐ this repo or share it with someone learning Data Analytics.🚀