customer-behaviour-analysis

data analytics project showcasing customer behaviour analysis using power bi ,sql and python Here’s a clean, professional, recruiter-friendly README.md you can directly paste into your project:

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📊 Data Analytics End-to-End Project

🔎 Overview

This project demonstrates a complete end-to-end Data Analytics workflow — from raw data processing to business insights and dashboard reporting.

The objective of this project is to:

• Load and process raw data using Python
• Perform Exploratory Data Analysis (EDA) and data cleaning
• Store and query data using SQL (PostgreSQL)
• Build an interactive Power BI dashboard
• Generate a structured analytical report
• Create a presentation using Gamma

This project showcases practical skills in data analysis, SQL querying, business intelligence, and reporting.

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📁 Dataset

• Source: (https://surl.li/aspzsj)

• Format: CSV

• Size: 3900

• Features include:

  • Numerical variables
  • Categorical variables
  • Date/time columns
  • Business KPIs

The dataset was cleaned and structured before analysis.

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🛠 Tools & Technologies Used

Category	Tools
Programming	Python
Libraries	Pandas, NumPy
Database	PostgreSQL
SQL	Joins, Aggregations, CTEs, Window Functions
Visualization	Power BI
Reporting	MS Word / PDF
Presentation	Gamma

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⚙️ Project Workflow / Steps

1️⃣ Data Loading (Python)

• Imported dataset using Pandas
• Inspected structure and data types
• Checked missing values and duplicates

2️⃣ Exploratory Data Analysis (EDA)

• Statistical summary
• Distribution analysis
• Correlation analysis
• Outlier detection
• Trend and pattern discovery

3️⃣ Data Cleaning

• Handled missing values
• Removed duplicates
• Standardized formats
• Feature engineering where required

4️⃣ SQL Analysis

• Loaded cleaned data into database

• Wrote optimized SQL queries:

  • Aggregations (SUM, AVG, COUNT)
  • Joins
  • GROUP BY analysis
  • Subqueries
  • Window functions

• Extracted business insights using SQL

5️⃣ Power BI Dashboard

• Connected Power BI to SQL database
• Built interactive dashboards
• Created KPIs and visual insights
• Implemented filters and slicers
• Designed clean, business-ready visuals

6️⃣ Reporting & Presentation

• Structured business report summarizing:

  • Key insights
  • Trends
  • Performance metrics

• Created presentation slides using Gamma for stakeholder communication

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📊 Dashboard Highlights

The Power BI dashboard includes:

• KPI summary cards
• Revenue / performance trends
• Category-wise breakdown
• Geographic analysis (if applicable)
• Interactive filters
• Drill-down functionality

The dashboard enables decision-makers to quickly interpret data and identify actionable insights.

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📈 Key Results & Insights

• Identified top-performing categories/products
• Discovered trends and seasonal patterns
• Highlighted performance gaps
• Provided data-driven recommendations

This project demonstrates the ability to translate raw data into meaningful business insights.

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▶️ How to Run the Project

1. Clone the Repository

git clone <>
cd <project-folder>

2. Install Dependencies

pip install -r requirements.txt

3. Run Python Scripts

python eda_analysis.py

4. Setup Database

• Create database in PostgreSQL / MySQL / SQL Server
• Import cleaned dataset
• Run SQL queries provided in /sql folder

5. Open Power BI

• Open .pbix file
• Update database connection if needed
• Refresh data

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🎯 Skills Demonstrated

• Data Cleaning & Preprocessing
• Exploratory Data Analysis
• SQL Query Optimization
• Business Intelligence Reporting
• Dashboard Design
• Data Storytelling
• End-to-End Analytics Workflow

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📌 Conclusion

This project reflects a production-style data analytics pipeline — integrating Python, SQL, and Power BI to deliver business insights in a clear, structured, and decision-oriented manner.

It demonstrates both technical depth and business understanding, making it suitable for Data Analyst / Business Intelligence roles.