What is analystlab-africa-week-5-task-telco-customer-churn-analysis?

This project is a business analytics case study built around a classic problem: figuring out why customers leave a telecom company, known as churn. It was completed as a week five assignment for the AnalystLab Africa internship program, using a public dataset from Kaggle that was originally published by IBM Watson Analytics. The dataset covers 7,043 customers and tracks things like how long each person has been a subscriber, what services they pay for such as phone, internet, and streaming add ons, how they pay their bill, and whether they eventually canceled. Of those customers, about one in four had churned, well above what the project describes as a typical industry range. The work follows three stages. First, Microsoft SQL Server Express was used to explore the raw data, check column types, and look for missing or duplicate records without changing anything. Next, the data was cleaned and explored further in Microsoft Excel, fixing blank fields, standardizing column names, and calculating basic statistics like averages for tenure and monthly charges. Finally, the cleaned data was loaded into Power BI Desktop, where custom calculations and an interactive two page dashboard were built to visualize churn rates and the factors behind them. One finding highlighted in the project is that customers who left were often paying more per month than those who stayed, which the author reads as a sign of dissatisfaction rather than customers simply being priced out. This repository is best understood as a learning portfolio piece rather than a reusable software tool. There is no application to install or run. Its value is in the dashboard, report, and presentation deck it produced, and in demonstrating a structured analytics workflow moving from database exploration, to spreadsheet cleaning, to business intelligence visualization.