{"id":24366972,"url":"https://github.com/fabioba/netflix-analytics","last_synced_at":"2026-05-15T20:03:03.981Z","repository":{"id":273130699,"uuid":"912838992","full_name":"fabioba/netflix-analytics","owner":"fabioba","description":"Analyse personal Netflix usage","archived":false,"fork":false,"pushed_at":"2025-01-19T22:10:53.000Z","size":1542,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-08-06T13:42:50.509Z","etag":null,"topics":["airflow","astronomer","bigquery","google-cloud-platform","netflix","tableau"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/fabioba.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-01-06T13:54:50.000Z","updated_at":"2025-01-20T19:18:28.000Z","dependencies_parsed_at":"2025-08-06T13:32:48.557Z","dependency_job_id":null,"html_url":"https://github.com/fabioba/netflix-analytics","commit_stats":null,"previous_names":["fabioba/netflix-analytics"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/fabioba/netflix-analytics","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fabioba%2Fnetflix-analytics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fabioba%2Fnetflix-analytics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fabioba%2Fnetflix-analytics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fabioba%2Fnetflix-analytics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fabioba","download_url":"https://codeload.github.com/fabioba/netflix-analytics/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fabioba%2Fnetflix-analytics/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33077943,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-15T11:35:32.926Z","status":"ssl_error","status_checked_at":"2026-05-15T11:35:31.362Z","response_time":103,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["airflow","astronomer","bigquery","google-cloud-platform","netflix","tableau"],"created_at":"2025-01-19T01:10:55.623Z","updated_at":"2026-05-15T20:03:03.939Z","avatar_url":"https://github.com/fabioba.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# netflix-analytics\nAnalyze personal Netflix usage\n\n- [Goal](#goal)\n    - [Business Questions](#business-questions)\n- [Technical Guide](#technical-guide)\n    - [Data Flow](#data-flow)\n        - [Data Source](#data-source)\n        - [Data Storage](#data-storage)\n        - [Visualization](#visualization)\n\n\n## Goal\nThis project aims to analyze Netflix usage from the first day of subscription (April 2024) until the end of the year.\n\n### Business Questions\n- what are the most watched movie category?\n- how often did I watch movies per week?\n- what is the most engaged movie genre?\n\n## Technical Guide\nIn order to reach the goal these are the steps to follow to develop the system:\n1. ingest data from Netflix\n2. for each movie, extract the details (via the [TMDB](https://www.themoviedb.org/) API)\n3. create the star schema\n\n\n### Data Flow\n![img](documentation/img/data_flow_adj.png)\n\n\n#### Data Sources\n- Netflix data: the dataset extracted at the end of 2024 is related to the movies streamed on the platform (title, date of stream)\n- TMDB API: extract movie details (release date, genre, ...)\n\n#### Data Storage\n- Google Cloud Storage: store the RAW data (data lake)\n- Google BigQuery: load raw data and transform (star schema)\n\n```\n- DIM_MOVIE: ID_MOVIE (PK)\n- DIM_GENRE: ID_GENRE (PK)\n- FCT_STREAMING: FCT_STREAMING_ID (PK)\n- BRIDGE_MOVIE_GENRE: ID_MOVIE (FK), ID_GENRE (FK)\n```\n\n![img](documentation/img/physical_model.png)\n\n#### Visualization\nThe outcome of the star schema is a layer that is read from [this](https://public.tableau.com/app/profile/fabi5755/viz/NetflixAnalytics_17372167014910/Dashboard1#1) dashboard on Tableau.\n![img](documentation/viz/dashboard.png)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffabioba%2Fnetflix-analytics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffabioba%2Fnetflix-analytics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffabioba%2Fnetflix-analytics/lists"}