Terraform module to create AWS Redshift resources 🇺🇦

This project builds a cloud-based ETL pipeline for Sparkify to move data to a cloud data warehouse. It extracts song and user activity data from AWS S3, stages it in Redshift, and transforms it into a star-schema data model with fact and dimension tables, enabling efficient querying to answer business questions.

Beginner data engineering project - batch edition

IMDB Movie Data ETL Pipeline using S3, Glue, Redshift, EventBridge, SNS

Airflow orchestrated ETL (running in docker containers) that pulls batch data from an API to a local Postgres database, loads to AWS S3/Redshift provisioned by Terraform, and visualized in Quicksight.

The data is collected from IMDB and then transformed before loading to warehouse

This project is a data warehousing solution for Sparkify, a music streaming service to extract data from JSON logs and stores it in a star schema data model in Amazon Redshift.

Deploy an Amazon Redshift Cluster in AWS using Terraform

Data Warehouse with AWS Redshift and Visualizing data using Power BI

Sparkify - Data Pipelines with Airflow - Udacity Data Engineering Expert Track.

ETL Pipeline from AWS S3 to Redshift

Reference code and projects for Udacity's Data Engineering Nanodegree. Graduated Jun 2020.

data pipeline ETL using Apache Airflow form data movement and amazon s3-storge with redshift cluster to storing the data in fact and DEM teables

AWS Pipeline examples from Udacity Date Engineering Nanodegree.

This project builds a pipeline from AWS S3 storage to a Redshift Cloud hosted Cluster where an ETL process extracts the staged data and creates a STAR Schema to allow business users to query the data easier for business intelligence.

Data Pipeline with Apache Airflow

Udacity Data Engineering Nanodegree Project 3

Database Schema & ETL pipeline for Song Play Analysis | Bosch AI Talent Accelerator Scholarship Program

Python ETL pipeline to load data from Amazon S3 to Redshift analytics tables