Xee-xainab/AnalystLab-Africa-Week-5-Telco-Customer-Churn-Analysis-Power-BI

Power BI business analytics project analyzing customer churn using Power Query, DAX, and interactive dashboards to identify churn drivers and provide actionable business recommendations. # 📊 Telco Customer Churn Analysis ## 📌 Project Overview This project analyzes customer churn in a telecommunications company using **Power BI**, **Power Query**, and **DAX**. The objective is to identify the key factors influencing customer churn, uncover actionable business insights, and provide data-driven recommendations to improve customer retention. This project was completed as part of the **Week 5 Business Analytics Case Study** during the **AnalystLab Africa Data Analytics Internship Program**. --- ## 🎯 Business Problem Customer churn is a major challenge for telecommunication companies because retaining existing customers is more cost-effective than acquiring new ones. Understanding why customers leave enables businesses to improve customer satisfaction, strengthen retention strategies, and increase long-term profitability. This project answers the following business questions: - Why are customers leaving the company? - Which customer segments are most likely to churn? - What factors contribute most to customer churn? - What strategies can reduce customer churn? --- ## 📂 Dataset Information - **Dataset:** Telco Customer Churn Dataset - **Source:** IBM Sample Dataset (Kaggle) - **Total Records:** 7,043 Customers - **Total Features:** 21 Columns The dataset includes customer demographics, subscription details, billing information, contract type, internet services, payment methods, tenure, monthly charges, and customer churn status. --- ## 🛠️ Tools & Technologies - Microsoft Power BI - Power Query - DAX (Data Analysis Expressions) - Microsoft Excel - Microsoft PowerPoint - Microsoft Word --- ## 🧹 Data Cleaning Data cleaning was performed using **Power Query** to ensure data quality before analysis. The following steps were completed: - Verified data types - Checked for missing values - Replaced the missing value in the **Total Charges** column - Checked for duplicate records - Converted **Senior Citizen** values from **0/1** to **No/Yes** - …