Catalino Ong

Comprehensive analysis of online retail data to identify sales trends, customer behavior patterns, and revenue optimization opportunities using advanced analytics.

Machine learning model to predict customer churn using historical data, achieving 85% accuracy with feature importance analysis and actionable insights.

Interactive Power BI dashboard for financial KPI tracking, budget analysis, and performance monitoring across multiple departments with real-time updates.

Comprehensive EDA framework to explore data structure, identify key characteristics, and uncover potential relationships using statistical methods and visualizations.

Interactive Tableau dashboard analyzing Electric Vehicle market trends, charging infrastructure, adoption rates, and geographic distribution patterns.

Comprehensive analysis of Netflix's content library exploring content distribution, genre trends, geographic patterns, and rating insights using Python.

Python-based analytics tool analyzing Instagram engagement metrics, follower growth patterns, post performance, and audience demographics insights.

Machine learning analysis of Spotify track features to predict song popularity, identifying key audio characteristics that drive music success.

Strategic sales analysis optimizing Coca-Cola's revenue forecasting, regional performance tracking, and market penetration strategies.

Medical imaging analysis using K-Means clustering for brain tissue segmentation, abnormality detection, and automated medical diagnosis support.

Natural Language Processing system for automated BBC news categorization, sentiment analysis, and content organization using advanced NLP techniques.

Advanced web scraping system enhanced with Large Language Models for intelligent data extraction, parsing, and automated content processing.

Educational analytics system analyzing student performance patterns, identifying at-risk students, and providing data-driven insights for academic improvement.

Comprehensive Formula 1 racing database analysis using SQL for driver performance tracking, team statistics, race results, and historical comparisons.

This analysis project explores Uber Eats data to gain insights into customer behavior, delivery patterns, restaurant performance, and ML techniques.

This data analytics project combines Python, machine learning, and Tableau to analyze US credit data, providing insights into credit risk, borrower behavior, and economic trends.

This project analyzes Fitbit activity data to gain insights into fitness patterns, sleep quality, and overall health metrics.

A Python-based project that analyzes real estate data and applies machine learning techniques to predict property prices, identify investment opportunities, and uncover market trends.

This project analyzes airline data using Python and machine learning techniques to extract insights about flight performance, customer satisfaction, pricing trends, and operational efficiency.

A real-time vision counter is a computer vision application that detects and counts objects in a live video stream.

This approach helps business and investors make data-driven decisions by leveraging predictive analytics.

Adidas sales data can be useful for a variety of purposes, such as analyzing sales trends, identifying successful products or marketing campaigns, and developing strategies for future sales.

This dashboard is a centralized management tool for hosts to track and optimize their rental properties.

A project focused on extracting insights from Amazon product reviews using Natural Language Processing (NLP) and data visualizations.

A project focused on extracting insights from Amazon product reviews using Natural Language Processing (NLP) and data visualizations.

A Python-based machine learning system for detecting fraudulent transactions or activities using various ML algorithms.