netflix-dataset

Análisis y visualización de datos con R de historial de actividad en Netflix de una cuenta personal. Visualización de maratones de series más vistas y frecuencia de actividad por días, meses y años

Production-style Netflix data lakehouse platform built on AWS, implementing a Medallion (Bronze–Silver–Gold) architecture to transform raw data into analytics-ready datasets. The pipeline leverages AWS Glue for scalable ETL processing, S3 as a data lake storage layer, Athena for serverless SQL analytics & Automated Glue workflows for Orchestration.

A notebook for movie and TV show recommendations using Boolean and TF-IDF methods. Get personalized suggestions based on text descriptions and choose the method that suits your preferences.

Netflix Flow

This is the Netflix Analysis till 2021 mid, done using Python. Read the "readme" file for a quick overview of the conslusions.

SQL project analyzing Netflix's movie & TV show catalog — from database design and data cleaning to 22 business questions covering content trends, genres, countries, and directors. Built in PostgreSQL.

Interactive Power BI dashboard analyzing Netflix's content portfolio, genre saturation, market opportunities, lifecycle trends, and data-driven investment strategies.

Netflix data analysis and visualization project using Python, Pandas, and Matplotlib to explore content trends, ratings, and distribution patterns.

Data warehousing project from identifying business opportunities, researching for data, designing, data modeling, performing data Extraction, Transformation, Loading using Python, building analytics in Tableau and made recommendations to optimize business strategies. Netflix is not only a successful Service But it is completely a Data-Driven

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.

SQL analysis of Netflix's content catalog using PostgreSQL — exploring ratings, genres, runtime, and cast/crew trends across a two-table relational schema (5,850 titles, 77,800+ credits).

A Python program that reads your Netflix viewing and billing data and shows you fun stats. Built for CS50P at Harvard.

Analyzing Netflix content trends using Python for data cleaning and Flourish Studio for interactive storytelling.

Netflix Data Analysis based on Age Based Ratings and Top Genres of 2021 of Movies - TV Shows along side Data Visualization

Stock Price Prediction

EDA of Netflix Dataset in Julia

This project performs Exploratory Data Analysis (EDA) on the Netflix Movies and TV Shows dataset to uncover trends in content distribution, growth patterns, genres, and audience targeting. The analysis focuses on transforming raw data into meaningful insights using data cleaning, visualization, and statistical reasoning

A production-ready Movie Recommendation Engine built with Collaborative Filtering (SVD Matrix Factorization) using scikit-surprise, containerized and deployed with a responsive Gradio web interface on Hugging Face Spaces.

Performed Analysis and Visualization on the NETFLIX TV SHOWS AND MOVIES Dataset. Data taken from Kaggle ( https://www.kaggle.com/datasets/shivamb/netflix-shows). @RaofaizanAPSACS