This project presents an interactive Power BI dashboard focused on Netflix's extensive library of movies and TV shows. With over 8000+ titles available on their platform, the dashboard offers insights into key details such as cast, directors, ratings, release year, and duration.

The Netflix data analysis model, developed using the powerful combination of NumPy, Pandas, and Plotly, serves as a valuable tool for extracting meaningful insights from the streaming platform's vast dataset. This model enables users to explore and analyze various aspects of Netflix's content library, user engagement, and viewer preferences.

A comprehensive exploration of Netflix movies & TV shows and mobile datasets, featuring univariate, bivariate, and multivariate analyses. Visualizations and insights showcase trends, correlations, and patterns in the data.

EDA and visualizations conducted over the Netflix dataset.

The Netflix Data Analysis Dashboard, created with Power BI and Excel CSV files, visualizes streaming trends, viewership patterns, and popular genres. It offers interactive insights into audience demographics and content ratings, enabling informed decision-making to optimize content strategy and drive engagement on the Netflix platform.

Data Analytics on Netflix data, creating valueable insights.

This SQL project provides an analytical overview of Netflix's movies and TV shows dataset, uncovering key insights related to content types, ratings, release trends, and geographic distribution. It helps explore patterns in content availability, audience targeting, and regional preferences to support data-driven decisions.

A data analysis project using Python to explore, visualize, and understand trends in Netflix's global content catalog — from genres and durations to ratings, release years, and countries.