Data Management at Scale: Modern Data Architecture with Data Mesh and Data Fabric

I’ve read a lot of books on data strategy and architecture but Data Management at Scale is the first one that truly mirrors the kinds of challenges I face in my day job. If you’re working in data leadership in a large complex organization, especially a multinational with messy value chains and siloed systems, this book will speak your language. Strengholt doesn’t waste time with vague frameworks. He gets into the real structural problems: how to build data products around business domains, how to design landing zones that actually scale, and how to put governance in place without killing agility. The chapter on Data Product Management alone is worth the price of the book. If you’re in a role where you’re trying to operationalize data strategy across functions, integrate governance into platform thinking, or just make data work across markets, this book is genuinely useful. It’s not aspirational fluff. It’s grounded, specific, and clearly written by someone who’s been through it.

A bunch of poorly structured encyclopedia knowledge mixed with hyped concepts. The author is not making innovation, introducing new concepts, nor carrying opinions of his own, but throws at you a compilation of what’s out there in the internet. Not engaging and very hard to read.

Well written, lots of very pragmatic information.

This was great book on data management. I enjoyed the details and learning about data mesh and domain data and data projects. API was good too.

I liked the book at it presents the data decentralization not merely as a technical matter, but as business transformation - something often gets forgotten. The author looks at the new roles that would emerge from data decentralization, organisational design patterns (also called "domain topologies", as they represent varios formats of relatonship between domains and central IT) and the role of vendor platforms in the new architecture called data mesh. I recommend it to anyone who wants to get a big picture of data decentralization, be it C-level executives, enterprise architects, agile specialists or data architects.

I bought this for educational purposes, whereas it's more of a biased intervention concept presented with academic contexts. It has a place, and is well written, but not what I needed!

From my perspective, the author fails to get to the point. The writing is repetitive and highly abstract, and it often lacks a clear conclusion or concrete recommendations. The topics are described in great detail and are certainly relevant, but they do not come together to form a coherent picture. For me, the book has no clear narrative thread, which frequently leaves me wondering why I am reading the flowery storytelling at all. The diagrams and examples also remain very superficial. I still give it 2 out of 5 stars because it contains a large number of keywords, references, and cross-references. I eventually started skimming the text for interesting buzzwords and then looking up more concise content online. I do not understand which target audience this book is written for. It reads more like a light novel than a technical or professional book.