Analyzed 6,000+ Netflix titles in Power BI using a star schema to explore genres, countries, ratings, and 70-year release trends. Built an interactive dashboard with KPIs, slicers, and drill-through visuals to compare movies vs TV shows and highlight top-rated and region-specific content. 📊 Netflix Data Analysis & Visualization | Power BI Overview
This project analyzes 6,000+ Netflix titles using Power BI to uncover trends in genres, countries, ratings, and release patterns over 70 years. The goal is to present a clear, interactive view of Netflix’s global content library using a clean data model and insightful visuals.
Power BI
Power Query
DAX
Star Schema Modeling
Data Cleaning & Transformation
The dataset includes:
Title, Type (Movie/TV Show)
Genre(s)
Country
Release Year
Duration
IMDb Rating & Votes
Cleaned and transformed raw data in Power Query.
Handled missing values such as age certifications.
Split multi-valued fields (genres, countries) into separate dimension tables.
Built a star schema with fact & dimension tables for efficient querying.
Interactive visuals covering:
Genre and country distribution
Release trends over 70 years
Movie vs TV Show performance
Runtime and rating patterns
KPIs: total titles, average rating, runtime stats
Slicers: year, type, genre, country
Drill-through pages: top directors, top countries, content subtypes
Clear peaks in content production across decades.
Genre popularity varies significantly by country.
Movies and TV shows differ in rating distributions and vote volumes.
Identified top-rated titles and the regions producing the most content.