Netflix Shows and Movies analysis Project

Tools Used

Excel, MySQL

Business Problem

Netflix aims to extract actionable insights from their vast dataset comprising approximately 82,000 rows of shows and movies. However, they face the challenge of effectively analyzing this extensive data to uncover valuable patterns and trends for their subscribers.

Solution Approach

To assist Netflix in deriving valuable insights from their extensive dataset, I propose leveraging SQL for data extraction and analysis. Using SQL functions, we can extract key metrics such as viewer ratings, popularity trends, genre preferences, and viewership patterns from the dataset.

Methodology

1. Data Extraction and Preparation: Utilize SQL queries to extract relevant information from the Netflix dataset.

2. Insightful Analysis: Employ SQL functions to analyze the data and derive meaningful insights.

Conclusion

Exploring various aspects of the dataset provided a comprehensive understanding of Netflix's content landscape. The analysis revealed insights into the top 10 and bottom 10 movies and shows based on their IMDB scores, highlighting titles with high praise and areas for potential improvement in content quality.

Examining movies and shows across different decades showcased significant shifts in content availability over time, with a notable increase in offerings from the 2000s onwards, reflecting Netflix's commitment to featuring newer content aligned with current trends and audience preferences.

Age certifications played a crucial role, influencing both the average IMDB scores and the distribution of movies and shows. The analysis revealed audience preferences for specific age certifications, with TV-14 garnering the highest average score, indicating its popularity among viewers.

Furthermore, exploring the most common genres in Netflix's library provided insights into viewer preferences and content distribution. Comedy emerged as the dominant genre across both movies and shows, followed by documentation and drama. Combinations of genres were also frequent, highlighting the audience's appreciation for multi-genre content.