NETFLIX CONTENT ANALYSIS
OVERVIEW
Netflix is a leading global streaming service offering a vast library of TV shows, movies, and original content. Known for its personalized recommendations and award-winning productions, Netflix operates on a subscription-based model, accessible on multiple devices worldwide. Despite increasing competition, it remains a dominant force in the streaming industry, continuously expanding its global presence and content offerings.
PURPOSE
The Netflix Data Analysis Project delves into the platform's extensive content catalog, examining genres, release dates, ratings, and viewer preferences to uncover trends and insights. By leveraging data-driven exploration, it aims to inform strategic decisions for Netflix and content creators, shedding light on evolving entertainment consumption patterns and audience preferences in the digital age.
OBJECTIVE
This project aims to provide data-driven insights that answer business questions and illuminate how viewership on the Netflix platform has impacted audiences worldwide.
Analysis Summary
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The Project Took 5 - 8 weeks to complete
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Netflix Data Set
2008 - 2023 -
Excel, PostgreSQL,Tableau
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Refining data, developing Entity Relationship Diagrams, employing queries, subqueries, and common table expressions, generating visualizations, and crafting presentations.
Analytical Approach
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Refining data, exploring its intricacies, summarizing findings, visualizing insights, and crafting compelling narratives.
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In addition to renaming and standardizing values, the data cleaning process may involved deduplication, handling missing values, correcting errors, normalizing data formats, and ensuring data integrity through validation checks.
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Used queries, subqueries and common table expressions to get descriptive statistics and answer business questions.
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Created visualizations using Tableau, and crafted presentations in PowerPoint for stakeholders or consumers to review and engage with the data.
Conclusion & Recommendation
Limitations
Invest more in less common but high-earning genres like International Drama, Sci-fi, Animation, and Sports.
Allocate resources for advertising and promotion in countries with the highest earnings like India, China, and the United States.
The data set has limited data from the earlier launch of the company.