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📊 Amazon Prime Content Analytics Dashboard

📌 Project Overview

The Amazon Prime Content Analytics Dashboard is an interactive dashboard built using Microsoft Excel to analyze Amazon Prime Video's content library. The project transforms raw data into meaningful insights using Excel's data analysis and visualization capabilities.

The dashboard helps identify trends in content types, genres, ratings, release years, and country-wise distribution, enabling data-driven decision-making.


🎯 Business Problem

Streaming platforms host thousands of movies and TV shows, making it challenging to understand content distribution and identify business trends.

This dashboard answers key questions such as:

  • What type of content dominates Amazon Prime?
  • Which genres are the most popular?
  • Which countries contribute the most titles?
  • How has the content library grown over time?
  • What audience ratings are most common?

📂 Dataset Information

  • Dataset: Amazon Prime Movies & TV Shows
  • Source: Kaggle – Amazon Prime Movies & TV Shows Dataset
  • Total Records: 9,668
  • Content Types: Movies & TV Shows

Dataset Columns

  • Show ID
  • Type
  • Title
  • Director
  • Cast
  • Country
  • Date Added
  • Release Year
  • Rating
  • Duration
  • Genre
  • Description

🛠 Tools Used

  • Microsoft Excel
  • Pivot Tables
  • Pivot Charts
  • Excel Map Chart
  • Slicers
  • Conditional Formatting
  • Excel Formulas (COUNTIF, SUMIFS, IF, etc.)

🧹 Data Cleaning

The dataset was prepared using Microsoft Excel by:

  • Removing duplicate records
  • Handling missing values
  • Formatting date fields
  • Standardizing country names
  • Verifying data types
  • Organizing the data for analysis

📊 Dashboard Features

KPI Cards

  • Total Titles
  • Total Movies
  • Total TV Shows
  • Top Country
  • Top Genre
  • Content Period

Visualizations

  • 🌍 Total Shows by Country (Map Chart)
  • 📈 Top 10 Ratings by Total Shows
  • 📅 Total Shows by Release Year
  • 📊 Top 10 Genres
  • 🥧 Movies vs TV Shows Distribution

📈 Key Insights

  • Amazon Prime contains 9,668 titles.
  • Movies account for approximately 81% of the catalog.
  • TV Shows represent approximately 19% of the content.
  • Drama is the leading genre, followed by Comedy and Action.
  • Most titles were released after 2015, indicating rapid content growth.
  • The United States contributes the highest number of titles.
  • The 13+ rating is the most common audience classification.
  • Amazon Prime features content from numerous countries, showcasing a globally diverse catalog.

💡 Business Recommendations

  • Continue investing in high-performing genres such as Drama and Comedy.
  • Expand content acquisition and production in emerging markets.
  • Increase family-friendly content based on audience rating trends.
  • Monitor yearly release trends to optimize future content strategies.

📷 Dashboard Preview

Dashboard


📁 Project Structure

Amazon-Prime-Content-Analytics-Dashboard/
│
├── Amazon prime Data Analysis Dashboard.xlsx
├── Dashboard.png
└── README.md

💼 Skills Demonstrated

  • Data Cleaning
  • Data Analysis
  • Data Visualization
  • Dashboard Design
  • KPI Development
  • Pivot Tables
  • Pivot Charts
  • Excel Map Charts
  • Business Intelligence Reporting
  • Business Insight Generation

🚀 How to Use

  1. Clone or download this repository.
  2. Open Amazon prime Data Analysis Dashboard.xlsx in Microsoft Excel (Excel 2019 or Microsoft 365 recommended).
  3. Navigate to the Dashboard worksheet.
  4. Explore the interactive dashboard and insights.

📌 Future Improvements

  • Add interactive slicers for Genre, Country, and Release Year.
  • Perform Director-wise and Actor-wise analysis.
  • Build monthly content growth trends.
  • Compare Amazon Prime content with Netflix and Disney+ datasets.

📜 Conclusion

This project demonstrates how Microsoft Excel can be used to perform end-to-end data analysis and build an interactive business dashboard. It showcases practical skills in data cleaning, dashboard design, KPI reporting, visualization, and business storytelling.


👨‍💻 Author

Sreevidya Yalla

Aspiring Data Analyst

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