UDRA introduces data mesh principles to flatten and simplify the Army’s data architecture, streamline data product sharing across mission partners, and support data-driven decision making at greater speed and scale.
This practical guide offers step-by-step guidance on how to implement data mesh in your organization.
Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse.
With this practical book, you’ll learn how to design a next-gen data architecture that takes into account the scale you need for your organization.
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.
Data mesh addresses these dimensions, founded in four principles: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a platform, and federated computational governance.
