Data Science: The Hard Parts by Daniel Vaughan (ISBN 978-1-098-14647-4)
← Previous: LLMs and the Future of Data Science
Seventeen chapters. Two parts. One preface that sets honest expectations. This series retold Daniel Vaughan’s Data Science: The Hard Parts chapter by chapter. Time to step back and say what stuck.
Data Engineering for Beginners by Chisom Nwokwu (ISBN 9781394325412, Wiley 2025)
Previous: Interview Questions Appendix
Thirteen chapters, an interview appendix, and a glossary later, here is where Data Engineering for Beginners lands.
The C++ Programmer’s Mindset by Sam Morley (ISBN 978-1-83588-842-1)
Fifteen chapters, one rubber duckies mystery, and a lot of code later, here is where The C++ Programmer’s Mindset lands.
Book: Data Engineering with AWS: A Comprehensive Guide to Building Robust Data Pipelines
Author: Brian Paul
ISBN: Not listed in the source edition
Book: Data Pipelines with Apache Airflow
Authors: Bas Harenslak, Julian deRuiter
ISBN: 9781617296901
Twenty-five posts later, I have read the whole book. Here is where I landed.
Book: Data Engineering with Python
Author: Paul Crickard
ISBN: 978-1-83921-418-9
Publisher: Packt (October 2020)
I finished the full walkthrough. Fifteen chapters, one appendix, two big projects, and a lot of terminal time. Here’s where I landed.
And that’s a wrap. We made it through all 10 chapters of “Learn Data Structures and Algorithms with Golang” by Bhagvan Kommadi. Here’s what I think after spending time with this book.
And that’s it. Eighteen posts. Thirteen chapters. One complete walkthrough of “Data Engineering for Beginners” by Chisom Nwokwu.
When I started this series, I said I wanted to retell the book in my own words. Not a summary, not a copy. My take on what each chapter covers and why it matters. Now that I’m at the end, let me step back and share my overall impressions.
Twenty-two posts later, we are done. This was my retelling of “Data Engineering with Google Cloud Platform” by Adi Wijaya (2nd edition, Packt Publishing, 2024, ISBN 978-1-83508-011-5). Time to look back, share what stuck with me, and give an honest assessment.
Nineteen posts. Sixteen chapters. One book. And here we are at the end.
When I started this retelling of Data Science Foundations: Navigating Digital Insight by Stephen Mariadas and Ian Huke (ISBN: 978-1-78017-6994, BCS 2025), I was not sure how it would go. Some books lose steam halfway. Some start strong and fizzle. But this one stayed consistent from first chapter to last.
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.
So here we are. Sixteen posts later and I’m done retelling “Learning Systems Thinking” by Diana Montalion. Time to wrap it up with what actually stuck with me.