This project consists of creating a database schema and an ETL pipeline from a music streaming app collected data.
The data resides in a directory of JSON logs containing user activity as well as JSON metadata on the songs.

. ##file structure

├──run.sh

├──src

│ ├── create_tables.py

│ ├── etl.py

│ ├── sql_queries.py

├──input

│ ├── data

│ ├── log_data

│ ├── song_data

##Runing the ETL

-executing run.sh will run create_tables.py then etl.py

-create_tables.py: the creation of schema structure into the postgres database

-etl.py:main ETL process

-the JSON logs resides in the input directory

• Name: songplays
• Type: Fact table

• Name: users
• Type: Dimension table

• Name: songs
• Type: Dimension table

• Name: artists
• Type: Dimension table

• Name: time
• Type: Dimension table

##How to run: -Make the script executable with command chmod +x run.sh -Run the script using ./run.sh