Название: Data Mesh: Delivering Data-Driven Value at Scale (Third Early Release)
Автор: Zhamak Dehghani
Издательство: O’Reilly Media, Inc.
Год: 2021-09-07
Страниц: 90
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice.

Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how.

Data Mesh is a new approach in sourcing, managing, and accessing data for analytical use cases at scale. Let’s call this class of data, analytical data. Analytical data is used for predictive or diagnostic use cases. It is the foundation for visualizations and reports that provide insights into the business. It is used to train Machine Learning (ML) models that augment the business with data-driven intelligence. It is the essential ingredient for organizations to move from intuition and gut-driven decision-making to taking actions based on observations and data-driven predictions. Analytical data is what powers the software and technology of the future. It enables a technology shift from human-designed rule-based algorithms to data-driven machine-learned models. Analytical data is becoming an increasingly critical component of the technology landscape.

Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures
Analyze the landscape's underlying characteristics and failure modes
Get a complete introduction to data mesh principles and its constituents
Learn how to design a data mesh architecture
Move beyond a monolithic data lake to a distributed data mesh