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The project digital music store case study using SQL. It includes analysis of various datasets such as Employee, Customer, Artist, Playlist, Playlist track, Album, Track, Invoice, media, genre etc with questions covering a range of difficulty levels from basic to advanced. A valuable resource for gaining deeper insights into SQL and data analysis.

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SarangGami/SQL_Project_Music_Store_CaseStudy

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SQL_Project_Music_Store 🎵 🎹

  • Case Study Of Digital Music Store using SQL

Database Tools

  • Postgre SQL
  • PgAdmin4

Table Of Contents

Introduction

In this project, we analyze a digital music store's data using SQL. The project includes a variety of questions that cover different aspects of the data, ranging from easy to advance level.

Datasets used

  • Employee
  • Customer
  • Artist
  • Playlist
  • Playlist track
  • Album
  • Track
  • Invoice
  • InvoiceLine
  • MediaType
  • Genre

Entity Relationship Diagram

MusicDatabaseSchema

Case Study Questions

Easy level questions include:

  • Retrieving the senior most employee based on job title
  • Identifying the countries with the most invoices
  • Finding the top 3 values of total invoice
  • Identifying the city with the highest sum of invoice totals
  • Identifying the customer who has spent the most money

Moderate level questions include:

  • Retrieving the email, first name, last name, and genre of all rock music listeners
  • Finding the top 10 rock bands by total track count
  • Retrieving the track names that have a song length longer than the average song length

Advanced level questions include:

  • Retrieving the amount spent by each customer on artists
  • Finding the most popular music genre for each country
  • Identifying the customer that has spent the most on music for each country

Click here to view the solution of the case study!

About

The project digital music store case study using SQL. It includes analysis of various datasets such as Employee, Customer, Artist, Playlist, Playlist track, Album, Track, Invoice, media, genre etc with questions covering a range of difficulty levels from basic to advanced. A valuable resource for gaining deeper insights into SQL and data analysis.

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