Netflix movies and TV shows data was used and it was acquired from (https://raw.githubusercontent.com/kedeisha1/Challenges/main/netflix_titles.csv) This dataset consisted of 8810 rows and 12 columns

Netflix operates the over-the-top subscription video on-demand service, which includes original films and television series commissioned or acquired by the company, and third-party content licensed from other distributors. This project was born out of my curiosity to answers some lingering question which includes but not limited to:

Determining the top genre of shows Netflix releases

To determine what year netflix added the most content

Understanding the top demographics where netflix movies are predominantly produced

Determining what type of shows Netflix focuses on mostly

Tools used included; SQL, Microsoft Excel and Power BI

This methodology entails recognising inadequate data types, identifying absent values, resolving them accordingly, revising, eliminating, or substituting extraneous data, and building more columns and tables.

Movies was the most popular shows on Netflix with 70% while TV Shows gets 30%

Netflix released the highest numbers of contents in 2019 with a total of 2016 contents

The year in which most movies added on Netflix were released is in 2018 with a total of 1146 shows

The top 5 most popular genre on Netflix are Dramas, Comedies, Action & Adventure, Documentaries, Children & Family

The country with the most release is the United States of America with a total of 2812 shows

The visualisations are on this page as a pdf format, but you can also see & explore it on Power BI through the link below: Power BI: https://lnkd.in/ddNHRRdA

My participation in this project has been a learning experience, and I owe this to the massive dataset processed. It has increased my analytical proficiency and boosted my confidence in handling complex datasets. As we move forward, I am hopeful that additional analysis will be conducted on the project