livyc
covid-19-data-engineering-pipeline
| livyc | covid-19-data-engineering-pipeline | |
|---|---|---|
| 2 | 1 | |
| 3 | 22 | |
| - | - | |
| 0.0 | 5.3 | |
| over 1 year ago | 6 months ago | |
| Python | Python | |
| MIT License | MIT License |
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livyc
covid-19-data-engineering-pipeline
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COVID-19 data pipeline on AWS feat. Glue/PySpark, Docker, Great Expectations, Airflow, and Redshift, templated in CF/CDK, deployable via Github Actions
I've seen amazing projects here already, which honestly were a great inspiration, and today I would like to show you my project. Some time ago, I had the idea to apply every tool I wanted to learn or try out to the same topic and since then this idea has grown into an entire pipeline: https://github.com/moritzkoerber/covid-19-data-engineering-pipeline
What are some alternatives?
Traffic-Data-Analysis-with-Apache-Spark-Based-on-Mobile-Robot-Data - Mobile robot data were analyzed with Apache-Spark to extract five different statistical result such as travel time, waiting time, average speed, occupancy and density were produced.
awesome-chalice - Discover the power of AWS Chalice, the ultimate framework for crafting seamless Python serverless applications. With Chalice, you can effortlessly build and manage HTTPS APIs, create web apps using popular front-end toolkits, and serve as the backend for cross-platform desktop and mobile apps developed with Qt for Python.
Apache-Spark-Guide - Apache Spark Guide
F2-Data-Pipeline - Pipeline for Automated Updates of Kaggle's "Formula 2 Dataset"
pyDag - Scheduling Big Data Workloads and Data Pipelines in the Cloud with pyDag
dataall - A modern data marketplace that makes collaboration among diverse users (like business, analysts and engineers) easier, increasing efficiency and agility in data projects on AWS.
yaetos - Write data & AI pipelines in (SQL, Spark, Pandas) and deploy to the cloud, simplified
lambda2docker - Generate a Dockerfile from an AWS Lambda function
pyspark-on-aws-emr - The goal of this project is to offer an AWS EMR template using Spot Fleet and On-Demand Instances that you can use quickly. Just focus on writing pyspark code.