Data fabric is an emerging architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems. It is a centralized data architecture that serves authorized consumers with integrated, governed, fresh data for analytical and operational workloads. Data fabric combines key data management technologies such as data catalog, data governance, data integration, data pipelining, and data orchestration. It aims to create more fluidity across data environments, attempting to counteract the problem of data gravity, which is the idea that data becomes more difficult to move as it grows in size.
Data fabric is an integrated layer of data and connecting processes that utilizes continuous analytics over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of integrated and reusable data across all environments, including hybrid and multi-cloud platforms. It leverages both human and machine capabilities to access data in place or support its consolidation where appropriate. Data fabric should be compatible with various data delivery styles, including ETL, streaming, replication, messaging, and data virtualization or data microservices.
Data fabric is still in its infancy in terms of adoption, but its data integration capabilities aid businesses in data discovery, allowing them to take on a variety of use cases. It can help businesses investing in AI, machine learning, and other data-driven technologies. Data fabric democratizes data access across the enterprise, at scale, and provides a single, unified architecture with an integrated set of technologies and services designed to deliver integrated and enriched data at the right time, in the right method, and to the right data consumer in support of both operational and analytical workloads.
