CASE STUDY
Bank Customer Churn
Jaya Jaya Maju is a multinational corporation established in 2000, with a workforce of over 1,000 employees spread across the country. Despite its significant scale, the company still faces challenges in managing its workforce. This has resulted in a high attrition rate—the ratio of staff departures relative to the total headcount—exceeding 10%. The HR Department requires assistance in identifying the various factors driving this high turnover rate and seeks a business dashboard to monitor these factors on a continuous basis.
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.