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📊 Netflix Data Analytics Dashboard

🔎 Data Cleaning • Analysis • Interactive Visualization with Python & Power BI


🚀 Project Overview

This project demonstrates a complete Data Analytics workflow applied to the Netflix catalog dataset.

The objective is to transform raw content data into structured analytical insights and prepare it for an interactive Business Intelligence dashboard.


🎯 Business Objectives

  • 📊 Analyze Movies vs TV Shows distribution
  • 🎭 Identify dominant genres
  • 🌍 Analyze production countries
  • 🔞 Study age classification patterns
  • 📈 Track catalog evolution over time
  • 💡 Generate actionable business insights

🧹 Data Preparation & Transformation

  • Handling missing values
  • Removing duplicates
  • Normalizing multi-value columns (country, listed_in)
  • Date formatting & feature engineering
  • Exporting clean dataset for BI

📊 Analytical Visualizations

  • Bar Charts → Type, Rating, Genre, Country
  • Pie Charts → Movies vs TV Shows
  • Line Charts → Content evolution over time
  • Heatmaps → Multi-variable analysis

💡 Key Insights

  • Movies dominate the catalog.
  • Drama & Comedy are the most frequent genres.
  • Strong growth between 2015–2020.
  • Majority of content targets mature audiences.

👩‍💻 Author

Safa Nya
Data Analyst | Python | Business Intelligence

About

End-to-end Netflix catalog analysis using Python, Pandas, and Power BI. Includes data cleaning, visualization, and business insights generation.

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