Additional Resources
Additional Resources
Section titled “Additional Resources”Here are some additional resources to help you learn more about data engineering and related topics.
Online Courses
Section titled “Online Courses”Data Engineering
Section titled “Data Engineering”- Data Engineering Zoomcamp - Free data engineering bootcamp
- Data Engineering with Python - Coursera course
- Data Engineering on AWS - AWS-specific data engineering
Python for Data
Section titled “Python for Data”- Python for Data Science - Basic Python for data
- Python Data Structures - Data structures in Python
- Python for Everybody - Comprehensive Python course
Data Engineering
Section titled “Data Engineering”- “Designing Data-Intensive Applications” by Martin Kleppmann
- “Data Mesh” by Zhamak Dehghani
- “The Data Warehouse Toolkit” by Ralph Kimball
Python
Section titled “Python”- “Python for Data Analysis” by Wes McKinney
- “Clean Code in Python” by Mariano Anaya
- “Effective Python” by Brett Slatkin
Documentation
Section titled “Documentation”Tools and Frameworks
Section titled “Tools and Frameworks”Databases
Section titled “Databases”Blogs and Communities
Section titled “Blogs and Communities”Communities
Section titled “Communities”Practice Projects
Section titled “Practice Projects”Beginner Projects
Section titled “Beginner Projects”- Build a data pipeline to process weather data
- Create an ETL pipeline for e-commerce data
- Implement a data quality monitoring system
Intermediate Projects
Section titled “Intermediate Projects”- Build a real-time data pipeline with Kafka
- Create a data warehouse with dimensional modeling
- Implement a data lake architecture
Advanced Projects
Section titled “Advanced Projects”- Build a complete data platform
- Implement a data mesh architecture
- Create a real-time analytics system
Tools and Technologies
Section titled “Tools and Technologies”Data Processing
Section titled “Data Processing”Data Storage
Section titled “Data Storage”Data Quality
Section titled “Data Quality”Next Steps
Section titled “Next Steps”- Review the Prerequisites if needed
- Set up your Development Environment
- Start with Data Engineering Fundamentals