Telecom-churn-analysis

Predict churn and derive actionable strategies to retain users in a highly competitive telecom environment.

📊 Data Analysis Portfolio

This repository showcases two foundational data analysis projects using SQL and Python. Each project demonstrates data preparation, analysis, and visualization for real-world business scenarios.

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🗂️ Projects Overview

1. 📁 SQL Sales Data Analysis

File: SQL analysis.sql

🔍 Description:

A simple relational schema simulating a sales environment with customer and order data. The project includes:

• Schema creation (Customers, Orders tables)
• Sample data insertion
• JOIN queries to combine data
• Aggregate functions (SUM, GROUP BY) for regional sales analysis

📌 Key Skills:

• SQL Joins
• Data aggregation
• Database normalization
• Query optimization (basic)

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2. 📁 Telecom Churn EDA

File: EDA OF TELECOM CHURN.ipynb

🔍 Description:

This Jupyter Notebook performs Exploratory Data Analysis on a telecom churn dataset to understand customer behavior and identify churn patterns.

📊 Analysis Includes:

• Data cleaning and preprocessing
• Univariate and bivariate analysis
• Visualizations using Seaborn/Matplotlib
• Insights on factors contributing to customer churn

📌 Key Skills:

• Python (Pandas, NumPy)
• Data visualization
• Feature interpretation
• Business insights from churn analysis

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📌 How to Run

🔧 Requirements:

• Python 3.8+
• Jupyter Notebook
• Libraries: pandas, matplotlib, seaborn, numpy
• MySQL or any compatible SQL environment for the SQL project

▶️ Instructions:

1. Clone the repo:

   git clone https://github.com/your-username/data-analysis-portfolio.git
   cd data-analysis-portfolio

Open the Jupyter notebook:

jupyter notebook "EDA OF TELECOM CHURN.ipynb" Contact If you have any questions or feedback, feel free to connect: