Projects in Awesome Lists tagged with redshift-cluster

https://github.com/josephmachado/beginner_de_project

Beginner data engineering project - batch edition

airflow database docker emr engineering etl python redshift redshift-cluster spark

Last synced: 15 May 2025

https://github.com/terraform-aws-modules/terraform-aws-redshift

Terraform module to create AWS Redshift resources 🇺🇦

aws redshift redshift-cluster terraform-module

Last synced: 12 Apr 2025

https://github.com/servian/amazon-redshift-checklist

This checklist aims to be an exhaustive list of all elements you should consider when using Amazon Redshift.

amazon-redshift aws checklist redshift redshift-cluster redshift-spectrum

Last synced: 26 Oct 2025

https://github.com/dina-hosny/sparkify---data-pipelines-with-airflow

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

airflow aws data-engineering dataengineering etl pipline redshift redshift-cluster udacity

Last synced: 16 May 2026

https://github.com/rishavmehra/health-synth

Health Synth simplifies healthcare with unified data, automated notifications, and patient feedback and monitoring the reports for better care and efficiency.

aws grafana hackfrost2024 kestra prometheus python redshift-cluster s3-bucket slack telegram-bot

Last synced: 10 Apr 2026

https://github.com/maxinexiong/cloud-data-warehousing-with-aws-redshift

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.

aws-boto3 aws-redshift aws-s3 cloud-data-warehouse data-engineering data-warehouse data-warehousing dimensional-model dimensional-modeling etl etl-pipeline extract-transform-load infrastructure-as-code postgresql postgresql-database redshift-cluster

Last synced: 27 Feb 2026

https://github.com/joyceannie/data-warehouse-aws

A music streaming startup, Sparkify, has grown their user base and song database and want to move their processes and data onto the cloud. The 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. The objective of the project is to create an ETL pieline to build a datawarehouse . We extract data from S3, stage them in Redshift, and transform data into a set of dimensional tables for the analytics team to continue finding insights into what songs their users are listening to.

aws aws-s3 data-warehouse python3 redshift redshift-cluster