WHAT SHOULD I LOOK FOR IN A DATA FABRIC SOLUTION?
在数据结构解决方案中应当关注哪些方面？
The data fabric aims to simplify data complexity through automating data integration, data governance, and data processing. Tools for data fabric design and management include data pipelines with various integration styles; workflow management, orchestration and policy management; active metadata and machine learning (ML) augmented data management; augmented data cataloging; data virtualization.
As the data fabric increasingly spans data across multiple clouds, data centers, and edge systems, it typically is built with the help of container-based technologies (such as Kubernetes) and related services mesh technologies.
数据结构旨在通过自动化数据集成、数据治理和数据处理来简化数据复杂性。用于数据结构设计和管理的工具包括采用各种集成样式的数据管道；工作流管理、协调和策略管理；主动元数据和机器学习 (ML) 增强的数据管理；增强数据编目；数据虚拟化。
随着数据结构越来越多地涵盖跨多个云端、数据中心和边缘系统的数据，它通常借助基于容器的技术（例如 Kubernetes）和相关服务网格技术进行构建。