SONG PLAY ANALYSIS WAREHOUSE

Propose of the project

This project has been developed to warehouse the song listening behavior of the user of music streaming application for analytics purpose.

About datasets

The songs data & log data are in JSON format that are stored in Amazon S3

Tech stack

• Python
• Postgres
• AWS redshift
• Notion for project management
• Github for Version control

Usage manual

• Create dwh.cfg file to store information regarding aws
• Execute main.py to perform following actions in sequence
  • Drop tables if exists
  • Create tables
  • Loads data from S3 to staging tables
  • Loads data from staging tables to facts and dimension tables

Files description

The project consists of five major files

constants.py

This file consists of all constants of aws configuration

sql_queries.py

This file consists of all sql queries

create_tables.py

It performs operation using sql_queries

• Establish connection with database
• Drops table
• Creates table

etl.py

This program consists of two methods for

• Loading data from S3 to staging tables
• Inserting data to the facts and dimensional table from staging tables

main.py

This program is a complete pipeline to

• Drop the existing tables
• Create the new tables
• Load the data to staging tables
• Insert the data to facts and dimension tables