Data Mesh : Delivering Data-Driven Value at Scale by Zhamak Dehghani (2022, Trade Paperback)
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Informazioni su questo prodotto
Product Identifiers
PublisherO'reilly Media, Incorporated
ISBN-101492092398
ISBN-139781492092391
eBay Product ID (ePID)7050388816
Product Key Features
Number of Pages384 Pages
LanguageEnglish
Publication NameData Mesh : Delivering Data-Driven Value at Scale
Publication Year2022
SubjectSoftware Development & Engineering / Quality Assurance & Testing, Systems Architecture / Distributed Systems & Computing, General, Software Development & Engineering / Project Management
TypeTextbook
AuthorZhamak Dehghani
Subject AreaMathematics, Computers
FormatTrade Paperback
Dimensions
Item Height0.8 in
Item Weight23.7 Oz
Item Length9.1 in
Item Width7.1 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2023-276385
Dewey Edition23
IllustratedYes
Dewey Decimal005.7
SynopsisWe'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