Description
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
Shipping, Return & Exchange
Shipping & Delivery:
– Normal Delivery: Estimated delivery time is 5 to 7 business days from the date of shipment.
– Express Delivery: Estimated delivery time is 3 to 5 business days from the date of shipment.
Returns & Exchange:
– Please refer to our Return and Exchange Policy for more details.
Patrick Hollowell –
A very insightful book on modern data architecture. It explains the data mesh concept in a practical way and shows how organizations can scale analytics effectively.
Scott Langley –
Well written and forward-thinking. The ideas around domain ownership and decentralized data are explained clearly.
Jerome Whitman –
A practical introduction to designing scalable, data-driven systems. The examples make complex ideas easier to grasp.
Carl Beaumont –
This book presents a fresh perspective on managing data at scale. The real-world concepts and architectural guidance are very useful for data teams.
Russell Davenport –
A strong guide for professionals exploring new approaches to data platforms. The explanations of principles and implementation challenges are valuable.
Colin Strathmore –
Very informative and thought-provoking. It gives a solid understanding of how organizations can manage data as a product and scale effectively.