https://github.com/master-helix/music-queries
This is a beginner Data Analyst Portfolio Project aimed at providing data insights based on a music store dataset
https://github.com/master-helix/music-queries
data-analytics data-visualization ms-excel postgresql sql
Last synced: 10 months ago
JSON representation
This is a beginner Data Analyst Portfolio Project aimed at providing data insights based on a music store dataset
- Host: GitHub
- URL: https://github.com/master-helix/music-queries
- Owner: Master-Helix
- Created: 2025-02-18T14:32:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-18T14:46:05.000Z (over 1 year ago)
- Last Synced: 2025-05-30T12:48:04.515Z (about 1 year ago)
- Topics: data-analytics, data-visualization, ms-excel, postgresql, sql
- Homepage:
- Size: 523 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🎵 Music Queries
This is a Beginner Data Analyst Portfolio Project aimed at providing data insights based on a music store dataset
## 🚀 Features
- Optimized SQL queries for music databases.
- Queries for song metadata, album details, and artist insights.
- Aggregation, filtering, and trend analysis queries.
- Performance optimized for large datasets.
## 🛠️ Installation & Setup
1. Clone the repository:
```bash
git clone https://github.com/Master-Helix/Music-Queries.git
```
2. Open your SQL environment (MySQL, PostgreSQL, etc.).
3. Import the sample music database (if required).
## 📊 Usage
- Run queries in your SQL environment to fetch insights from the music database.
- Modify queries based on your dataset structure.
- Explore different patterns in music trends.
## 📂 Overview of the Queries Included
- Retrieve the top 10 most played songs.
- Find albums released in a specific year.
- Get the most popular artists by number of streams.
- Analyze genre-based song distribution.
## 📜 Contributing
Contributions are welcome! You can fix this repository, create a new branch, and submit a pull request.
---
✨ Enjoy your data analytics journey and please contribute a start if you liked it. Thanks. :)✨