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.