Power BI dashboard analyzing 3.4K+ web series (2000–2024) across 42 countries, 96 industries, and 70M+ votes.
An interactive data analytics dashboard built to analyze content distribution, ratings, genres, and trends on Prime Video.
An end-to-end data analytics and forecasting project analyzing YouTube series performance, audience retention, engagement trends, and geographic distribution to predict future growth and optimize content strategy.
Content ROI and Genre Profitability is a data analytics project focused on evaluating content performance across different Genres and Platforms using financial and engagement metrics
Predictive modeling for early success forecasting of movies using Video-On-Demand streaming data, featuring Gradient Boosting Machines and advanced feature engineering techniques.
Okkax - platform terpadu yang menghubungkan penyelenggara, talent, venue, vendor, sponsor, tenant, pekerja, ticketing, pembayaran, dan operasional event dalam satu sistem.
Predictive analysis of Japanese media IP to optimise global market expansion.
This repository provides a comprehensive Exploratory Data Analysis (EDA) of entertainment content, revealing trends in relation to audience preferences, production locations, release patterns and content duration.
🎬 Interactive Netflix content analytics — exploring genre trends, release patterns, and country-wise distribution across 8K+ titles.
Comprehensive SQL analysis of Netflix content library with 15 advanced queries exploring movies vs TV shows, ratings, genres, directors, actors, and regional content distribution.
Interactive JioHotstar Content Analytics Dashboard built with Power BI, Python, Numpy, Pandas, Plotly, Pillow, and Streamlit, featuring content trends, genre analysis, ratings insights, and global distribution analytics.
Tableau dashboard analyzing IMDb movie data — genre popularity, decade-wise trends, director performance, rating distributions, and runtime patterns across cinema history.
A comprehensive Power BI dashboard providing analytical insights into movie industry data including box office performance, ratings, genres, director/actor metrics, and trends. Analyzes budget vs revenue, release timing impact, and audience preferences.
Interactive Tableau dashboard analyzing Amazon Prime content, genres, ratings, release trends, and geographic distribution.
A machine learning project that predicts movie success in two ways: financial blockbusters (top 25% by revenue) and popularity blockbusters (top 25% by audience score). It compares multiple models to understand what drives each type of success.
A Python-based calibration project for estimating Non-Drama H-Score weights for Korean variety and entertainment shows. K-예능/쇼 프로그램의 흥행 가능성을 예측하기 위한 Non-Drama H-Score 6축 가중치 캘리브레이션 프로젝트 ⬇자세한 분석
Machine learning pipeline for predicting movie box office success. Includes web scraping, data pipelines, feature engineering, ML models, MLflow tracking, and a web interface for predictions.
Interactive analysis of Prime Video movies and TV shows exploring ratings, genres, countries, directors, and release-year trends.
Find out what's TikTok algorithm to post and get more viewers
Exploratory Data Analysis on Netflix Movies and TV Shows dataset.
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