{"id":18087874,"url":"https://github.com/swethajoseph/rsvp-movies-sql-case-study","last_synced_at":"2026-04-28T01:33:10.347Z","repository":{"id":260363981,"uuid":"881089066","full_name":"SwethaJoseph/RSVP-Movies-SQL-Case-Study","owner":"SwethaJoseph","description":"An SQL-based analysis of IMDb data to guide RSVP Movies’ Global expansion, focusing on genre trends, release timing, and top industry talent","archived":false,"fork":false,"pushed_at":"2024-11-05T11:46:10.000Z","size":6272,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-06T01:43:59.756Z","etag":null,"topics":["dataanalysis","dataexploration","datavisualization","mysql","sql-server"],"latest_commit_sha":null,"homepage":"","language":null,"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/SwethaJoseph.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}},"created_at":"2024-10-30T22:25:06.000Z","updated_at":"2024-11-05T11:46:13.000Z","dependencies_parsed_at":"2025-02-12T07:44:51.584Z","dependency_job_id":"20e71172-9488-431a-a484-a891864f7d0b","html_url":"https://github.com/SwethaJoseph/RSVP-Movies-SQL-Case-Study","commit_stats":null,"previous_names":["swethajoseph/rsvp-movies-sql-case-study"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwethaJoseph%2FRSVP-Movies-SQL-Case-Study","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwethaJoseph%2FRSVP-Movies-SQL-Case-Study/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwethaJoseph%2FRSVP-Movies-SQL-Case-Study/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwethaJoseph%2FRSVP-Movies-SQL-Case-Study/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SwethaJoseph","download_url":"https://codeload.github.com/SwethaJoseph/RSVP-Movies-SQL-Case-Study/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247423496,"owners_count":20936622,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["dataanalysis","dataexploration","datavisualization","mysql","sql-server"],"created_at":"2024-10-31T17:09:14.211Z","updated_at":"2026-04-28T01:33:10.302Z","avatar_url":"https://github.com/SwethaJoseph.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# RSVP-Movies-SQL-Case-Study\n## Overview\nThis project is an SQL-driven analysis aimed at supporting RSVP Movies, an Indian film production company, as it prepares for a global movie release in 2024. By examining trends in movie genres, release timing, ratings, and industry success factors, the analysis provides data-backed insights that inform strategies for a successful international launch.\n\n## Dataset Description\nThe project uses data from the IMDb database covering movie releases between 2017 and 2019. The dataset includes information on:\n\n* Movie: Movie details such as title, release year, country, duration, and worldwide gross income.\n* Genre: Genre classification for each movie.\n* Ratings: Average rating, median rating, total votes, and other rating metrics.\n* Names: Data on actors, directors, and other key personnel involved in each movie.\n* Director \u0026 Role Mapping: Mapping tables to connect movies with their respective directors and actors.\n  \nThe dataset has been processed using SQL to answer strategic questions regarding genre performance, ratings, and global audience preferences.\n\n## ENTITY- RELATIONSHIP DIAGRAM (ERD)\nThe ERD below illustrates the relationships between the key tables used in this project:\n\n![Entity-Relationship Diagram](ERD.png)\n\n* Download the IMDB Dataset: Ensure all necessary tables (movies, genres, ratings, contributors) are accessible.\n* Review Data Structure: Study the relationships and schema in the ERD to understand the data connections.\n* Set Up the Database: Use your preferred SQL environment (e.g., MySQL Workbench) to create and populate the database using the provided SQL scripts or custom commands.\n\n_Note: If you’d like to skip the manual setup, a SQL script is available that automates database creation and data loading._\n\n## Objectives\n* Identify Popular Genres: Determine the best-performing genres for RSVP’s new release.\n* Timing Insights: Find optimal release months based on historical trends.\n* Ratings \u0026 Performance: Assess ratings distribution and identify top-rated movies, actors, and directors.\n* Global Trends: Compare performance metrics in major markets like the USA and India.\n* Production Recommendations: Offer strategic guidance on selecting top production houses, actors, and directors for international appeal.\n\n## Analysis Segments\n\n1. **Movie Release Trends**\n* Annual and Monthly Release Patterns: Analyzed the trend of movie releases by year and month, with March showing the highest release frequency.\n* Country-Specific Insights: Identified that the USA and India are the top producers, collectively releasing 1,059 movies in 2019 alone.\n\n2. **Genre Insights**\n* Top Genres: Drama emerged as the most produced genre, followed by Thriller and Action.\n* Genre Duration: Action movies have the longest average duration, while Horror is the shortest, with most genres averaging between 100-110 minutes.\n\n3. **Rating Analysis**\n* Rating Range: Most movies receive ratings from 1 to 10, with no significant outliers, suggesting a balanced rating distribution.\n* Top-Rated Movies: The highest-rated movies, including \"Kirket\" and \"Love in Kilnerry,\" achieved an average rating of 9.5.\n* Production House Performance: Dream Warrior Pictures and National Theatre Live rank as top production houses, each producing three highly-rated movies.\n\n4. **Performance by Contributors**\n* Top Directors: Identified top directors like James Mangold, Joe Russo, and Anthony Russo, whose movies have an average rating above 8.\n* Top Actors and Actresses: Mammootty and Mohanlal emerged as leading actors with high median-rated movies, while Taapsee Pannu was the top actress in Hindi films.\n\n5. **Box Office Success**\n* Top-Grossing Movies: Movies like \"Avengers: Endgame\" and \"The Lion King\" dominated the box office, especially in the Action and Adventure genres.\n* Production House Influence: Marvel Studios and Warner Bros. are top producers, excelling in box office revenue and audience appeal.\n\n## Findings \u0026 Recommendations\n* Focus on High-Performing Genres: Drama, Action, and Thriller genres show high engagement and should be prioritized for international release.\n* Optimal Release Timing: Aim for a March release, which historically has the highest number of movie releases.\n* Top Talent Collaboration: Collaborate with top-rated directors and actors, such as Vijay Sethupathi and directors like James Mangold, to maximize global appeal.\n* Box Office Insights: Leverage popular production houses like Marvel Studios for their market influence and experience with high-grossing movies.\n\n## Tools \u0026 Technologies\n* MySQL Workbench or any SQL Editor: For querying and analyzing the IMDb dataset.\n* Microsoft Excel: For initial data processing and visualization.\n* PowerPoint: To present findings and strategic insights.\n\n## Contact\nFor further questions or suggestions, feel free to reach out to [LinkedIn | Swetha Kizhavana Joseph](https://www.linkedin.com/in/swetha-kizhavana-joseph-04b68721b/) or [email](swethakjoseph16@gmail.com) \n### If you found this project helpful or interesting, please give it a ⭐ to show your 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