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Analyzing Netflix Data for Business Insights

Okogie Timothy's photo
Okogie Timothy
·

2 min read

INTRODUCTION

Netflix is one of the world's leading entertainment services with over 232 million paid memberships in over 100 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as many times as they want, anytime, anywhere, and can change their plans at any time. Our dataset is once again obtained from kaggle (https://www.kaggle.com/datasets/shivamb/netflix-shows).

PROBLEM STATEMENT

Project Description:

As a data analyst, your task is to analyze Netflix data to derive insights that can help the company make informed business decisions. The project will involve analyzing various data sets, including customer viewing patterns, ratings, and preferences, as well as data on Netflix's content library.

Objectives:

  • Identify the most popular shows and movies on Netflix based on viewership data.

  • Analyze viewer behavior and preferences to understand which genres and types of content are most popular.

  • Investigate the relationship between user ratings and viewership data to understand how ratings impact viewership.

  • Evaluate the performance of Netflix's original content versus licensed content. Identify potential areas for growth and expansion for the company.

Deliverables:

  • A report summarizing the key insights gained from the analysis, including visualizations and charts to aid in understanding.

  • A presentation highlighting the most important findings and recommendations for the business

Data Importation & Cleaning

Data was imported from MS Excel (as a .csv file). The data was cleaned in Power query. Cleaning involved removing errors and removing duplicates. It was also necessary at some point to reduce redundancy by removing some empty fields in the data.

Data Analysis and Visualization

Due to the limited data obtained from this particular dataset, analysis was done based on Movies and TV shows contents by countries. Also, a filter was added to show countries, so as to know what kind of content is available in those countries. The original PowerBI file containing visualizations and analysis can be found here

Conclusion

From the analysis, a larger part of the Netflix content is movies which accounts for over 80% of the total video contents of this dataset. Some countries actually had more movies than TV shows while some others had more TV shows than movies (The US and UK in direct comparison here). Also, it could be observed that during Covid-19, the number of TV shows increased in comparism t the number of movies released.

Team Members include members of SideHustle data analytics team 11 - Moradeyo Simisola Opeyemi , Yusuff Habeeb , Sophia Asafa-Idowu (aka Pride of Africa)

@Ngsidehustle