Empower decision-makers with an interactive Power BI dashboard showcasing e-commerce performance metrics and trends. Analyze sales data, forecast future trends, and drive informed strategies for business growth.

Web scraper for collecting product and review data from e-commerce sites using Scraping Bee, AWS, Selenium, and Pandas. Focuses on cost-effective solutions, user-friendly interfaces, and efficient data extraction and analysis.

Comprehensive EDA Portfolio showcasing data analysis expertise across diverse domains including e-commerce, healthcare, real estate, retail, and finance. This repository demonstrates proficiency in Python, data visualization, statistical analysis, and business intelligence using real-world datasets from Kaggle.

A Flask-based machine learning web app that predicts furniture sales using product details, price, and shipping info with interactive visual insights.

🔸 Customer Segmentation Analysis 🔸 Performed Customer Segmentation Analysis on an e-commerce dataset using clustering techniques (K-Means). Cleaned, explored, and visualized customer data to uncover spending patterns and demographic insights. Delivered actionable insights for targeted marketing strategies and customer retention.

Proyek Submision Dicoding Indonesia - Belajar Analisis Data dengan Python

Performed cohort analysis to boost retention & revenue via SQL insights on customer retention, revenue retention, & CLV by product category, with actionable strategies for high-value categories.

Segment Sphere is a customer segmentation tool using RFM analysis to group customers based on recency, frequency, and monetary value. It processes e-commerce data, provides actionable insights, and visualizes results with interactive charts. Ideal for understanding customer behaviour and supporting data-driven decisions.