{"id":26868894,"url":"https://github.com/cintia0528/data_analytics-advanced_sql","last_synced_at":"2026-01-11T02:24:39.714Z","repository":{"id":212276491,"uuid":"731105536","full_name":"Cintia0528/Data_Analytics-Advanced_SQL","owner":"Cintia0528","description":"Revisiting SQL skills, enhancing with CTEs, functions, and window functions. Analyzing IMDB and Magist databases, expanding with web-scraped data.","archived":false,"fork":false,"pushed_at":"2023-12-14T12:00:49.000Z","size":54,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-31T05:35:16.793Z","etag":null,"topics":["advancedsql","cte","stored-procedures","windowfunc"],"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/Cintia0528.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}},"created_at":"2023-12-13T11:18:23.000Z","updated_at":"2024-02-26T05:31:52.000Z","dependencies_parsed_at":"2023-12-14T13:26:50.801Z","dependency_job_id":"e498d6f8-2b0c-4346-9286-5693e89ea0b1","html_url":"https://github.com/Cintia0528/Data_Analytics-Advanced_SQL","commit_stats":null,"previous_names":["cintia0528/project-9-advanced-sql","cintia0528/project-10-advanced-sql","cintia0528/data_analytics-advanced_sql"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Cintia0528%2FData_Analytics-Advanced_SQL","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Cintia0528%2FData_Analytics-Advanced_SQL/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Cintia0528%2FData_Analytics-Advanced_SQL/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Cintia0528%2FData_Analytics-Advanced_SQL/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Cintia0528","download_url":"https://codeload.github.com/Cintia0528/Data_Analytics-Advanced_SQL/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246423503,"owners_count":20774796,"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":["advancedsql","cte","stored-procedures","windowfunc"],"created_at":"2025-03-31T05:35:19.311Z","updated_at":"2026-01-11T02:24:39.005Z","avatar_url":"https://github.com/Cintia0528.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# In-Depth-Data-Analysis-with-SQL\n\n# Goal\nThe primary aim of this project is to conduct an in-depth analysis of two databases—IMDB and Magist employing advanced data analytics techniques, including stored functions and processes, CTEs (Common Table Expressions), and window functions. \n**The overarching goal is to enhance analytical efficiency, reduce time and cost, and pave the way for future data analysts to expedite their processes.**\n\n# Overview\nThis repository showcases my analytical prowess on two distinct databases. \n1. The first involves a comprehensive analysis of the IMDB database, utilizing advanced SQL tools and functions to streamline analytics processes and ensure a thorough understanding of the dataset.\n2. The second part involves revisiting the Magist database from Project 1 , where I not only expand the analysis but also demonstrate a **full-circle application of skills**, including creating new tables, integrating them into the existing database, and implementing stored functions and processes for a holistic database mastery.\n\n# Approach\n## IMDB Database Analysis:\n- Conducted a detailed examination of the IMDB database.\n- Implemented advanced SQL techniques, such as Stored Functions and Processes, CTEs, and Window Functions.\n- Prioritized the creation of stored functions and processes to enhance long-term time and cost savings.\n\n## Magist Database Revisit:\n- Revisited the Magist database, building upon the analysis performed in a previous project.\n- Expanded the database by creating new tables and seamlessly integrating them into the existing structure.\n- Applied stored functions and processes to ensure a comprehensive and efficient analytical approach.\n- Demonstrated raw data transformation for a deeper understanding of the dataset.\n\n# Deliverables\nThe project includes:\n- [IMDB analysis questions](https://github.com/Cintia0528/Project-9-Advanced-SQL/blob/67c3f6585884f2e7749c7404b61f645727216db5/IMDB%20questions%20-%20Advanced%20SQL.pdf) and corresponding [SQL code](https://github.com/Cintia0528/Project-9-Advanced-SQL/blob/67c3f6585884f2e7749c7404b61f645727216db5/imdb_analysis.sql).\n- Magist analysis questions and corresponding SQL code.\n\n# Skills \u0026 Tools\n- **In-Depth Analysis:** Thorough examination of datasets to derive meaningful insights.\n- **Stored Functions and Processes:** Implementation of procedures for long-term time and cost savings.\n- **CTE's (Common Table Expressions):** Leveraging CTEs for efficient and readable SQL queries.\n- **Window Functions:** Employing window functions for advanced analytics.\n- **Raw Data Transformation:** Manipulating raw data to extract valuable information.\n- **Database Expansion:** Extending database structure through the creation of new tables and integration of analytical processes.\n\n# Further Analysis\nTo enhance the project:\n- Explore the possibility of incorporating additional advanced SQL features.\n- Consider optimizing queries for better performance.\n- Collaborate with data analysts to gather feedback for continuous improvement.\n- Document and share insights on a broader platform, such as a Medium article, to contribute to the community's knowledge base.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcintia0528%2Fdata_analytics-advanced_sql","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcintia0528%2Fdata_analytics-advanced_sql","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcintia0528%2Fdata_analytics-advanced_sql/lists"}