Project to demonstrate the Airflow capabalities by loading data from S3 to Redshift using Star schema
A music streaming company, Sparkify, has decided that it is time to introduce more automation and monitoring to their data warehouse ETL pipelines and come to the conclusion that the best tool to achieve this is Apache Airflow.
Technologies used
- Python3
- Apache Airflow
- AWS redshift
- AWS s3
Data Sources
Log data: s3://udacity-dend/log_data
Song data: s3://udacity-dend/song_data
Files and explantion create_tables.sql - Contains the DDL to create tables used in this projects udac_example_dag.py - The Airflow DAG file stage_redshift.py - Operator to load data from s3 to redshift load_fact.py - Operator to load the fact tables to redshift load_dimension.py - Operator to load dimension table data_quality.py - Operator for data quality check
Data quality is checked in the end of the DAG to verify data is loaded succesfllly