Project: Data Lake

Introduction

A music streaming startup, Sparkify, has grown their user base and song database even more and want to move their data warehouse to a data lake. Their data resides in S3, in a directory of JSON logs on user activity on the app, as well as a directory with JSON metadata on the songs in their app.

building an ETL pipeline that extracts their data from S3, processes them using Spark, and loads the data back into S3 as a set of dimensional tables. This will allow their analytics team to continue finding insights in what songs their users are listening to.

Project Description

In this project,i build data lakes & ETL pipeline for a data lake hosted on S3. by load data from S3, process the data into analytics tables using Spark, and load them back into S3.

How to run:

Replace AWS IAM Credentials in dl.cfg run python etl.py in the terminal