https://github.com/moritzkoerber/data-engineering-practice

My solutions to Daniel Beach's Data Engineering Practice Problems
https://github.com/moritzkoerber/data-engineering-practice

apache-spark aws data-engineering docker dockercompose duckdb pandas pipenv polars soda-sql

Last synced: about 2 months ago
JSON representation

My solutions to Daniel Beach's Data Engineering Practice Problems

• Host: GitHub
• URL: https://github.com/moritzkoerber/data-engineering-practice
• Owner: moritzkoerber
• License: mit
• Fork: true (danielbeach/data-engineering-practice)
• Created: 2022-03-06T00:06:25.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-17T16:56:26.000Z (3 months ago)
• Last Synced: 2024-09-24T18:32:23.238Z (about 2 months ago)
• Topics: apache-spark, aws, data-engineering, docker, dockercompose, duckdb, pandas, pipenv, polars, soda-sql
• Language: Python
• Homepage:
• Size: 45.3 MB
• Stars: 8
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
This repository contains my solutions to the awsome seven data engineering exercises by Daniel Beach (https://github.com/danielbeach/data-engineering-practice/).

To re-run the solutions, either

- use the Docker Compose files, or

- install the pipenv virtual environment and run the main.py module in each respective folder.