Chapter 4 is where you stop reading about components and actually start wiring them together. Laura Funderburk calls it “Bringing Components Together,” and that’s exactly what it is. You take all those building blocks from Chapter 3 and connect them into working pipelines.
Chapter 1 was about understanding data itself. Chapter 2 answers the bigger question: what do data engineers actually do with it?
Chapter 1 of Data Engineering with Python by Paul Crickard starts with the basics. What is data engineering? What do data engineers actually do? And how is it different from data science?
In the first part we got Cloud Composer running, wrote our first DAGs, and learned operators. This second part covers the stuff that separates beginner Airflow code from production-ready pipelines: variables, idempotent tasks, backfilling, sensors, and dataset-driven scheduling.
So I picked up Data Engineering with Python by Paul Crickard (Packt, 2020, ISBN: 978-1-83921-418-9) and decided to write up my study notes as I go through it. I’ve been working in IT for over 20 years, and data engineering keeps coming up everywhere. This book seemed like a good one to work through and share what I learn.
You built a model. It works. The numbers look great. But nobody uses it.
Because you forgot the people around it. Chapter 2 of “Data Science Foundations” by Stephen Mariadas and Ian Huke is about exactly that. Stakeholders. The humans who care about your project, fund it, get affected by it, or can shut it down.
In the first part we covered Haystack 2.0’s core ideas: components, pipelines, SuperComponents, and how hybrid retrieval works. Now let’s look at what happens when you hand these pipelines to an AI agent, plus the full catalog of component types Haystack gives you out of the box.
The book opens with a simple claim: data is the new oil. You’ve probably heard that phrase a hundred times. But Nwokwu doesn’t just drop the cliche and move on. She actually walks you through why that comparison holds up, starting from thousands of years ago.
I picked up “Data Engineering for Beginners” by Chisom Nwokwu (Wiley, 2026, ISBN: 9781394325412) a few weeks ago. I was looking for something that explains data engineering from scratch, without assuming you already know half the field. This book does exactly that.
Up until now in the book, we built BigQuery tables by hand, wrote queries in the console, and loaded data manually. That works for learning, but nobody does that in production. In production, you need things to run on their own, on schedule, without you babysitting them at 5 AM.