Data Mesh by Zhamak Dehghani

Data Mesh by Zhamak Dehghani

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

Zhamak Dehghani is a director of technology at ThoughtWorks, focusing on distributed systems architecture --- big data and operational systems -- in the enterprise. She's a member of the company's Technology Advisory Board and contributes to the creation of ThoughtWorks's Technology Radar. She is an advocate for decentralization of all things - architecture, data and ultimately power. She is the founder of data mesh.

SKU	Nicht verfügbar
ISBN 13	9781492092391
ISBN 10	1492092398
Titel	Data Mesh
Autor	Zhamak Dehghani
Buchzustand	Nicht verfügbar
Bindungsart	Paperback
Verlag	O'Reilly Media
Erscheinungsjahr	2022-03-22
Seitenanzahl	270
Hinweis auf dem Einband	Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
Hinweis	Nicht verfügbar