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 o...(展开全部)

本书介绍了数据网格——一种来自现代分布式架构的去中心化社会技术范式，它提供了一种大规模采购、共享、访问和管理分析型数据的新方法。 本书分为五部分。第1部分介绍Data Mesh的四个原则，以及它们所组成的高级模型。 第二部分比较Data Mesh与以前的数据架构的区别。 第三部分介绍Data Mesh组件的高层次架构，帮助你设计Data Mesh架构以及评估与Data Mesh匹配的现成技术。 第四部分介绍Data Mesh中的一个核心概念（数据产品）的详细设计，帮助你识别与Data Mesh愿景兼容的设计技术，并将它们与不兼容的技术区分开来。 第五部分介绍如何演进式地执行Data Mesh的转换，以及如何围绕团队结构、激励、文化等做出组织设计决策的可行建议。

本书介绍了数据网格——一种来自现代分布式架构的去中心化社会技术范式，它提供了一种大规模采购、共享、访问和管理分析型数据的新方法。 本书分为五部分。第1部分介绍Data Mesh的四个原则，以及它们所组成的高级模型。 第二部分比较Data Mesh与以前的数据架构的区别。 第三部分介绍Data Mesh组件的高层次架构，帮助你设计Data Mesh架构以及评估与Data Mesh匹配的现成技术。 第四部分介绍Data Mesh中的一个核心概念（数据产品）的详细设计，帮助你识别与Data Mesh愿景兼容的设计技术，并将它们与不兼容的技术区分开来。 第五部分介绍如何演进式地执行Data Mesh的转换，以及如何围绕团队结构、激励、文化等做出组织设计决策的可行建议。

As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a...(展开全部)

Organizations today often struggle when trying to balance business requirements with ever-increasing volumes of data. Yet the need to take advantage of real-time data continues to grow among the most competitive digital industries. Conventional system architectures may not be up to the task. With this practical guide, you’ll learn how to leverage large-scale data usage across t...(展开全部)

Organizations today often struggle when trying to balance business requirements with ever-increasing volumes of data. Yet the need to take advantage of real-time data continues to grow among the most competitive digital industries. Conventional system architectures may not be up to the task. With this practical guide, you’ll learn how to leverage large-scale data usage across t...(展开全部)

Large-scale data analysis ("Big Data") is suddenly of crucial importance to virtually every enterprise. Mobile and social technologies are generating massive datasets, and distributed cloud computing is providing better ways to analyzing and processing that data. Accelerating technological change is turning long-accepted ideas about Big Data upside down, forcing companies to ev...(展开全部)

Large-scale data analysis ("Big Data") is suddenly of crucial importance to virtually every enterprise. Mobile and social technologies are generating massive datasets, and distributed cloud computing is providing better ways to analyzing and processing that data. Accelerating technological change is turning long-accepted ideas about Big Data upside down, forcing companies to ev...(展开全部)

Summary How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, wit...(展开全部)