Data Mesh: Delivering Data-Driven Value at Scale

by: Zhamak Dehghani (0)

We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, author Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale.

Dehghani guides practitioners, architects, technical leaders, and decision makers on their journey from traditional big data architecture to a distributed and multidimensional approach to analytical data management. Data mesh treats data as a product, considers domains as a primary concern, applies platform thinking to create self-serve data infrastructure, and introduces a federated computational model of data governance.

  • Get a complete introduction to data mesh principles and its constituents
  • Design a data mesh architecture
  • Guide a data mesh strategy and execution
  • Navigate organizational design to a decentralized data ownership model
  • Move beyond traditional data warehouses and lakes to a distributed data mesh

The Reviews

This book is the missing manual. If you're in any data driven organization &/or managing an organization through a transformation with the goal to manage distributed data as products, this is a must read.The book is technology agnostic. What it does very well is lay out a very thorough map for what shape data, technologies & teams should look like, what functions they should fulfill & how they should all interoperate as a system to manage data as product successfully. It provides a somewhat idealized vision, but I'm all in as I've seen some of this in action & helped put some of these systems in place.At MarkLogic we helped organizations implement solutions that managed data as product. (I no longer work at MarkLogic & have nothing to gain here in promoting them, just sharing my experience.) MarkLogic integrated data from various silos within large organizations to create data products. Above the silos of data were silos of people that also required integrating. Change management was always a challenge. I recommend How Stella Saved the Farm & The Phoenix Project to help others start to understand the types of changes they need to embrace to succeed. But what was missing was the architectural guide. We made up for it with slides, white papers & tribal knowledge, but this Data Mesh book truly captures some of the best practices I saw organziations put into place.It's all here: start with the business goal and work your way back, data product as self-contained unit, the sidecar pattern, embedding policy as code, start small & fast for a big win, iterate, progressively enhance products, govern with provenance & lineage, the changing roles that support this endeavor, operational & analytical systems & the desired intertwingling, + more..We didn't use the term Data Mesh & didn't do everything captured here. The challenge with any vendor is we tend to think of ourselves as the center of the universe. MarkLogic's way to integrate with a larger world of data was Semantics. But #DataMesh provides a higher level of abstraction.The book's just really well done. Technology vendors don't know how to document like this. Vendors focus on their own product's knobs & levers. What they fail to understand & illustrate for their customers is that their particular technology works within a system of technologies to achieve a business goal. It never works alone. So I HIGHLY RECOMMEND this book. If you can grok the patterns outlined here, you can fill in the gaps with the technology, people & process right for your solution.

This book elaborate the origins of data mesh which is a response to ancient arquitectures like warehouses or data lakes (at the writing of this, not so ancient) and promise a better way to create value from data where other approaches have failed to do so.It's a recommended reading for developers, architects who want to implement or know how to design a system for data analytics and suited for an high volatile environment that needs to scale through time.The concepts presented along this book are technology-agnostic but it is useful to know some technologies about databases, cloud providers, and agile methodologies in order to have a better context, again not a must but useful.By the way the coloured brushes used for pictures made the reading enjoyable.

Zhamak Dehghani says “Data mesh is what comes after an inflection point, shifting our approach, attitude, and technology toward data. Mathematically, an inflection point is a magic moment at which a curve stops bending one way and starts curving in the other direction. It’s a point that the old picture dissolves, giving way to a new one.” Data Mesh, Chapter 6“A strategic inflection point is a time in the life of a business when its fundamentals are about to change. That change can mean an opportunity to rise to new heights. But it may just as likely signal the beginning of the end. — Andrew S. Grove” Data Mesh, Chapter 6In the Data Mesh book, Zhamak Dehghani does not refer only to the real world practices that reinforce the data mesh theory, but also stands on the generally accepted principles of Systems Thinking. Zhamak Dehghani referred to “Thinking in Systems” for Donnelly H. Meadows while talking about leverage points and feedback loops for maintaining Dynamic Equilibrium.

Obvious once written but obscured by years and years of siloed specialization Zhamak Dehghani brings data analytics back into the fold of proper software development principles. First and foremost Domain Driven development (Evans), in second order how to manage complexity. Highly recommended for every engineer and manager working in data-intensive applications at enterprise scale.

This book is simply a masterpiece. Zharmak has managed to author the rare book with actionable, provocative, and meaningful content for data management and governance. Do I agree 💯 with everything in here? Not necessarily. However, she makes her reasoning clear for an extremely strong case. If I could offer a criticism, I would ask to her to use language that is plain to the average data professional. However, it is digestible, especially if you take 3 or 4 chapters at a time. I can’t offer enough praise! You need this book. I’ll be watching for updates as well.

This book made me to realize that there actually aren't that many data books that provide a complete vision and not just focus on a limited set of functionality. Data Mesh is only partially about technology but has a lot to do with organizations, change management, empowering the right people and recognizing the domain specialists' needs. This book is not a blueprint of data platform but a blueprint of a data-driven organization which makes it mandatory read.

I didn't purchase the kindle version to have the colors available... The book is in black and white and the colors were crucial to understand the concepts. It feels like it will subtract lots of value to the book. Nothing to say about the content, just about the printing process

Data Mesh: Delivering Data-Driven Value at Scale
⭐ 4.5 💛 127
kindle: $43.99
paperback: $41.26
Buy the Book