This release contains the final version of my Customer Retention and Churn Analysis project, developed as a complete business analytics pipeline. The study investigates churn behaviour in a telecom company, beginning with raw data ingestion and relational database engineering in PostgreSQL, followed by structured SQL analysis, and culminating in an interactive executive dashboard built in Power BI. The analysis addresses the critical business question: "Why are customers leaving, which segments are most at risk, and what actions can the business take to improve retention?" Using a dataset where 26.54% of customers have churned (representing 1,869 lost customers), the project highlights behavioural and contractual drivers of churn and proposes targeted, data‑driven interventions to improve retention. This release includes reproducible code, database schema, SQL queries, and dashboard files, making it suitable for citation, replication, and practical application in subscription‑based industries.