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Status Power BI Excel Dataset

🎬 Netflix BI Dashboard

An interactive Power BI dashboard that analyzes Netflix’s global content catalog — including movies, TV shows, genres, ratings, release trends, and country-level distribution.

This project provides a visually rich and business-focused understanding of content production and release behavior on Netflix.


📌 Business Objective

The goal of this project is to help content & strategy teams answer:

  • How is Netflix expanding its library over time?
  • What types of shows (Movies vs TV Shows) dominate the platform?
  • Which content ratings are most common?
  • What genres does Netflix prioritize?
  • Which countries produce the most content?
  • For any selected movie/TV show:
    • What is its description?
    • Who directed it?
    • Who are the cast members?
    • What categories does it belong to?

The dashboard is designed for quick insights + detailed show-level exploration.


🧩 Dataset

Source: Kaggle – Netflix Movies and TV Shows Dataset

Files used:

File Purpose
titles.csv Core dataset with titles, year, rating, duration, type
listed_in.csv Categories / genres
cast.csv Actor names for each show
country.csv Country where the show was produced
description.csv Show summary

🔧 Excel Pre-processing

Because the dataset was split across multiple CSV files, Excel was used to:

  • Clean missing values
  • Normalize inconsistent text fields
  • Combine datasets using show_id
  • Prepare a final merged dataset for Power BI

🛠️ Tech Stack

  • Power BI Desktop
    • Data modeling
    • Relationship creation using show_id
    • Custom visuals + map charts
  • Microsoft Excel
    • Data cleaning
    • Combining multiple CSV files
  • GitHub
    • Documentation
    • Version control

🗂️ Data Model

The Power BI model uses 1-to-many relationships with show_id as the key:

titles (main table)
│── listed_in (genres)
│── director table
│── cast table
│── description
└── country table

This star-schema–like structure supports clean filtering across all dashboard visuals.

Model View


📊 Power BI Dashboard – Pages & Insights


📄 Page 1 – Show Details Viewer

A full show-level profile UI:

🔎 Search box

Select any movie/TV show (e.g., #Alive, Money Heist, Stranger Things).

📝 Show Information Card

  • Year Released
  • Rating
  • Description

🧩 Categorization Panels

  • Category (genre)
  • Directed by
  • Cast list

🌍 Shows Released by Countries (map)

  • Highlights which countries released that particular show
  • Red bubbles sized by count

Screenshot:

Show Details


📄 Page 2 – Netflix Global Insights Dashboard

A business-level overview of Netflix's entire catalog.

Screenshot:

Show Details

🎞️ 1. Shows Added by Date

  • Bar chart showing content count for each rating
  • TV-MA is the most frequent rating
  • Family-safe ratings show expected lower volume

Shows Added by Rating


🌐 2. Shows Released by Countries

  • Interactive world map
  • Large clusters in:
    • USA
    • India
    • UK
    • South Korea
    • Japan

Shows by Country


🎭 3. Top 10 Genres

  • Ranked bar chart showing genre popularity
  • Most dominant:
    • International Movies
    • Dramas
    • Comedies
    • Documentaries

Top 10 Genres


🎞️ 4. Shows Added by Rating

  • Bar chart showing content count for each rating
  • TV-MA is the most frequent rating
  • Family-safe ratings show expected lower volume

Shows Added by Rating


🧾 Key Features

✔ Interactive show search
✔ Dynamic filtering across director, cast, category
✔ World map visual for content distribution
✔ Time trend & rating-wise analytics
✔ Genre-level insights
✔ No DAX — clean visual modeling approach
✔ Excel-based data transformation

📁 Project Structure

Netflix-BI/
│
├── PowerBI/ → Dashboard PBIX (only snapshots)
├── excel/ → Cleaned & merged dataset (too large to include in github)
├── screenshots/ → Images for README
└── README.md

⭐ Outcome

This dashboard helps stakeholders and content analysts:

  • Understand global content trends
  • Identify genre opportunities
  • Find regional strengths
  • Analyze content maturity (ratings & release years)
  • Explore individual titles in rich detail

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