Data Engineering With Python: Final Thoughts and Takeaways
That’s it. Fifteen chapters, seventeen posts, and one complete walkthrough of Paul Crickard’s Data Engineering with Python (Packt, 2020, ISBN: 978-1-83921-418-9).
Apache nifi
Streaming Data With Apache Kafka - Study Notes From Data Engineering With Python Ch 13
Up to this point in the book, data pipelines have been about moving data that already exists. Query a database, read a file, process it, store it. The data sits still and you go get it.
Building a Production Data Pipeline - Study Notes From Data Engineering With Python Ch 11
You learned the individual tools. You learned the deployment strategies. Now Chapter 11 of Data Engineering with Python by Paul Crickard puts it all together. This is the chapter where you build a complete, production-grade data pipeline from start to finish.
Deploying Data Pipelines - Study Notes From Data Engineering With Python Ch 10
You built your data pipelines. They work on your laptop. Now what? Chapter 10 of Data Engineering with Python by Paul Crickard covers the part everyone eventually has to face: getting your pipelines out of development and into production.
NiFi Registry Version Control - Study Notes From Data Engineering With Python Ch 8
You’ve been building data pipelines for several chapters now. They work. They move data. But here’s the problem: none of them have version control. If you break something, there’s no going back. Chapter 8 of Data Engineering with Python by Paul Crickard fixes that. It introduces the NiFi Registry, a sub-project of Apache NiFi that handles version control for your data pipelines.
Building a 311 Data Pipeline - Study Notes From Data Engineering With Python Ch 6
The previous chapters taught you the individual tools. Python, NiFi, Airflow, databases, data cleaning. Chapter 6 of Data Engineering with Python by Paul Crickard puts them all together into one real project.
Building Your Data Engineering Setup - Study Notes From Data Engineering With Python Ch 2
Chapter 1 was all theory. Now it’s time to actually install stuff. Chapter 2 of Data Engineering with Python by Paul Crickard is a setup chapter. You install the tools, configure them, and make sure everything talks to each other.