Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Great book. Using it on daily basis. Gives you a comprehensive understanding of data Engineering fundamentals.

This is a great book for anyone who has a solid understanding of software development and cloud architecture, but doesn't have direct experience building data pipelines or data analytics products. The authors don't get into much technical detail at a tactical level - this is not a book about actually implementing anything whatsoever. Rather, this book offers a really excellent 10,000 foot view of the current state of Data Engineering from multiple angles. Throughout the book they spend a lot of time explaining the "people" side of things (what developers and teams actually do when building Data Eng teams, analytics pipelines, etc.) and how they interact with various other teams and stakeholders (data scientists, analysts, PMs, execs,...). They also cover a vast amount of ground on the architectural side of things. As a developer with years of tech experience, but one which has never directly worked on data pipelines, I really enjoyed how they offered both numerous examples and stories of how projects were built and operated in the _ancient_ "big data" Hadoop era (i.e. 2010-2020, LOL!), and then how quickly the tech and related architectures have changed as significant new technologies came to the fore (i.e. Kafka, BigQuery/Athena, Snowflake/Databricks, etc...). My 2 constructive criticisms of this book are: 1) Some will be frustrated by the lack of tactical content or technical depth. That said, what they sacrifice in depth they make up for in scope. The data analytics space is vast, and evolving at a breakneck pace. They do an admirable job of introducing and summarizing a vast topic, all grounded in practical advice and real-world anecdotes and examples (from their own professional experience). 2) They have 1 surprising blind spot, imho – which is that they don't even offer a passing nod to Domain Driven Design (DDD). Given that they do discuss topics including microservices, data models, schemas, and some aspects of "domains" in the enterprise sense, as well as the need to interact with stakeholders and experts from various other teams (aka "domain experts"), this strikes me as a surprising blind spot. I'd like to see them explore DDD in a future 2nd edition (please!). Final word – If you're an experienced developer or architect with big data or analytics experience, this book may leave you wanting. For anyone else with a solid technical foundation and an interest in the data realm from almost any angle, this is a great read that's well worth your time.

Every data engineer needs to read this book. The book provides good guidance on the big picture of data engineering, from the source system, storage, ingestion, transformation, serving as well as security, data management, data operation, data architecture, orchestration. And unlike any other technical book this book is a good read! Meaning it's engaging, like in a dialog with the readers. It gets me to think of what is really important. Thank you Joe Reis and Matthew Housley for writing it.

A little slow and the audible narration could be better but otherwise an OK book for someone wanting an extended overview of the topic.

I like the book very useful

Great

Absolutely top-notch! "Fundamentals of Data Engineering" by Joe Reis and Matt Housley is a masterstroke, providing a comprehensive and practical view of data engineering, a field that has seen rapid growth in recent years. This invaluable resource effortlessly breaks down complex concepts into easily digestible chunks, shedding light on the often-overlooked aspects of the field such as data generation, ingestion, orchestration, transformation, storage, governance, and deployment.

not sure what this book achieves at all but it has at least peaked into the total non sense the field of data engineering has become with proliferation of tools, ideas, architecture, and practices where every vendor is trying to capture a market share by making their product appear unique. No one actually cares as long as vendors and consultancies continue to suck budget out and fail in 3 to 4 yrs and a coverup of a new trend starts asking for more budget, you can peek into the history of coverups and failures and billions in losses for the last 10 years in this book

Muy bueno

I bought it as a gift for a friend of mine. He was happy about it, as long as he had been looking for this book for a while

I am a bit disappointed, the topics are described with no examples, everything is too high level

Es existiert leider viel zu wenig Standard Literatur zu dem Thema Data Engineering, Reis & Housley ändern das nun. Es bietet nicht nur Berufseinsteigern einen guten Überblick über den Themenkomplex Data Engineering, es bringt eben auch einen Konsens mit. Gewohnt von der guten Qualität von O'Reilly definitiv ein guter Kauf! Gerade mit Data Management at Scale finde ich das vermittelte Wissen echt spitze! Je nach Bedarf muss man natürlich dann in die Tiefe gehen :)

Goed geschreven boek dat de Fundamentals of Data Engineering inderdaad in de volle breedte gedegen behandeld. Auteurs hebben wel een sterke voorkeur voor cloud-oplossingen.