https://github.com/cintia0528/data_analytics-advanced_sql
Revisiting SQL skills, enhancing with CTEs, functions, and window functions. Analyzing IMDB and Magist databases, expanding with web-scraped data.
https://github.com/cintia0528/data_analytics-advanced_sql
advancedsql cte stored-procedures windowfunc
Last synced: about 1 month ago
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Revisiting SQL skills, enhancing with CTEs, functions, and window functions. Analyzing IMDB and Magist databases, expanding with web-scraped data.
- Host: GitHub
- URL: https://github.com/cintia0528/data_analytics-advanced_sql
- Owner: Cintia0528
- Created: 2023-12-13T11:18:23.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-12-14T12:00:49.000Z (about 2 years ago)
- Last Synced: 2025-03-31T05:35:16.793Z (11 months ago)
- Topics: advancedsql, cte, stored-procedures, windowfunc
- Homepage:
- Size: 52.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# In-Depth-Data-Analysis-with-SQL
# Goal
The 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.
**The overarching goal is to enhance analytical efficiency, reduce time and cost, and pave the way for future data analysts to expedite their processes.**
# Overview
This repository showcases my analytical prowess on two distinct databases.
1. 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.
2. 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.
# Approach
## IMDB Database Analysis:
- Conducted a detailed examination of the IMDB database.
- Implemented advanced SQL techniques, such as Stored Functions and Processes, CTEs, and Window Functions.
- Prioritized the creation of stored functions and processes to enhance long-term time and cost savings.
## Magist Database Revisit:
- Revisited the Magist database, building upon the analysis performed in a previous project.
- Expanded the database by creating new tables and seamlessly integrating them into the existing structure.
- Applied stored functions and processes to ensure a comprehensive and efficient analytical approach.
- Demonstrated raw data transformation for a deeper understanding of the dataset.
# Deliverables
The project includes:
- [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).
- Magist analysis questions and corresponding SQL code.
# Skills & Tools
- **In-Depth Analysis:** Thorough examination of datasets to derive meaningful insights.
- **Stored Functions and Processes:** Implementation of procedures for long-term time and cost savings.
- **CTE's (Common Table Expressions):** Leveraging CTEs for efficient and readable SQL queries.
- **Window Functions:** Employing window functions for advanced analytics.
- **Raw Data Transformation:** Manipulating raw data to extract valuable information.
- **Database Expansion:** Extending database structure through the creation of new tables and integration of analytical processes.
# Further Analysis
To enhance the project:
- Explore the possibility of incorporating additional advanced SQL features.
- Consider optimizing queries for better performance.
- Collaborate with data analysts to gather feedback for continuous improvement.
- Document and share insights on a broader platform, such as a Medium article, to contribute to the community's knowledge base.