An interactive Power BI dashboard analyzing customer churn for a telecom company, built to help executive leadership monitor churn, explore customer behavior, identify business risks, and support retention strategy. This project continues from the Week 1 (exploratory analysis) and Week 2 (BI dashboard fundamentals) work on the same dataset.
Week 3: Interactive Business Intelligence Dashboard & Executive Data Storytelling
AnalystLab Africa — Data Analytics Internship Programme
Overview
An interactive Power BI dashboard analyzing customer churn for a telecom company, built to help executive leadership monitor churn, explore customer behavior, identify business risks, and support retention strategy. This project continues from the Week 1 (exploratory analysis) and Week 2 (BI dashboard fundamentals) work on the same dataset.
Dataset
Telco Customer Churn Dataset (Kaggle) — 7,043 customer records.
What's in this repo
Telco_Customer_Churn_Cleaned.csv — cleaned dataset used in the dashboard
Week 3 Interactive Business Intelligence Dashboard & Executive Data Storytelling — the Power BI project file
Week 3 Interactive Business Intelligence Dashboard & Executive Data Storytelling.pdf — static export of all dashboard pages
Executive_Insights_Report.docx — key findings, churn drivers, and recommendations
DAX_Measures_Documentation.md — explanation of all 9 DAX measures used
Dashboard_Documentation.md — full dashboard overview, data model, and page descriptions
Key Findings
Overall churn rate: 26.5%
Month-to-month contracts churn at 42.7% vs. 2.8% for two-year contracts
Customers in their first 12 months churn at 47.4%
Electronic check payers churn at 45.3%, the highest of any payment method
Estimated revenue lost to churn: Ksh 2,862,927
See the Executive Insights Report for full analysis and recommendations.
Dashboard Pages
Executive Overview — KPI scorecards
Customer Insights — demographics vs. churn
Service & Churn — service subscriptions vs. churn
Revenue — financial impact of churn
Customer Detail — drill-through page
Tools
Power BI Desktop, DAX, Power Query
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