https://github.com/shubhamsoni98/analysis-with-sql

This project focuses on creating and managing a database for a music record company to perform various analyses on bands, albums, and songs. Using SQL, the goal is to create a structured relational database with relevant tables, insert necessary data, and perform queries that provide insights into the relationships between bands, albums, and songs.
https://github.com/shubhamsoni98/analysis-with-sql

analys analysis data data-science database dbms mysql mysqlworkbench project query schema sql

Last synced: 24 days ago
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This project focuses on creating and managing a database for a music record company to perform various analyses on bands, albums, and songs. Using SQL, the goal is to create a structured relational database with relevant tables, insert necessary data, and perform queries that provide insights into the relationships between bands, albums, and songs.

• Host: GitHub
• URL: https://github.com/shubhamsoni98/analysis-with-sql
• Owner: shubhamsoni98
• Created: 2024-09-11T15:41:22.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-11T15:59:39.000Z (about 2 months ago)
• Last Synced: 2024-10-13T02:06:09.944Z (24 days ago)
• Topics: analys, analysis, data, data-science, database, dbms, mysql, mysqlworkbench, project, query, schema, sql
• Homepage:
• Size: 28.3 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Analysis-with-SQL

This project focuses on creating and managing a database for a music record company to perform various analyses on bands, albums, and songs. Using SQL, the goal is to create a structured relational database with relevant tables, insert necessary data, and perform queries that provide insights into the relationships between bands, albums, and songs.

The project includes creating tables for bands, albums, and songs, maintaining foreign key relationships, and writing SQL queries to extract meaningful information such as identifying the oldest albums, longest songs, and bands with or without albums. Additionally, the project demonstrates the ability to manage database records by inserting, updating, and deleting data, along with performing aggregate operations like calculating average song lengths and filtering data by specific criteria.

# Key Steps:

**Database and Schema Creation:**

Created a new database and defined a schema with tables such as Bands, Albums, and Songs.

Established relationships between tables using foreign keys to maintain referential integrity.

**Data Population:**

Inserted data into the database using SQL scripts (schema.sql and data.sql), which include predefined records of bands, albums, and songs.

**Query and Data Analysis:**

Implemented SQL queries to analyze the data, such as:

Selecting all band names.

Identifying the oldest album.

Determining the bands with and without albums.

Finding the longest album and song.

Calculating the average length of songs.

Inserting and removing records.

Grouping data to count songs by band and finding the longest song per album.

**Database Management:**

Demonstrated the ability to modify the database by adding and dropping records, altering tables, and ensuring consistency with foreign key relationships.

**Technologies Used:**

**MySQL:** Database management system for creating and managing the relational database.

**SQL:** Structured Query Language for writing queries and managing the data.

**Project Outcomes:**

Created a robust database structure that efficiently organizes data about bands, albums, and songs.

Implemented various SQL queries for data retrieval and analysis, demonstrating the ability to manipulate data and extract useful insights.

Managed database integrity through foreign key relationships, ensuring accurate and meaningful analysis.