CASE STUDY
HR Analytics
This end-to-end data analytics project focuses on diagnosing and understanding customer churn within the banking sector. With a churn rate of 20% across 10,000 customers, the bank faced a critical challenge: retaining financially stable, long-term clients who were actively moving their capital to competitors. The analysis was conducted using the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology — moving beyond surface-level visualization into deep business understanding and strategic evaluation.
This project explores a massive-scale user interaction dataset (approx. 14GB) from a major Video-on-Demand (OTT) platform. The primary objective is to translate raw viewing logs into actionable business strategies across four key pillars: Marketing ROI, Technical User Experience (UX), Product Feature Effectiveness, and Content Monetization. By processing millions of rows using highly memory-efficient techniques, this analysis provides clear, data-driven recommendations to optimize ad spend, reduce churn rate, and maximize platform loyalty.
A comprehensive end-to-end data analysis project using Microsoft Power BI to diagnose business performance for Olist, a Brazilian e-commerce platform. This project analyzes over 100,000 transaction records to uncover the root causes of stagnant customer satisfaction scores. Key findings reveal critical bottlenecks in the logistics chain—specifically within carrier transit times—and highlight geographical disparities hindering market expansion. The dashboard provides actionable insights to optimize supply chain operations and improve customer experience.