Data Fabric is a new technology that offers an innovative, robust integration of data sources across platforms and business users, making data accessible wherever it is needed, regardless of where the data is located. It is an architectural way to simplify data access in an organization to facilitate self-service data consumption. This architecture is agnostic to data environments, processes, utility and geography, all with enabling end-to-end data-management capabilities. A data fabric automates data discovery, governance and consumption, enabling enterprises to use data to maximize their value chain. Below the article lists five advantages of using Data Fabric technology.

Smart Integration: The aim of data fabric is to unify data across different data types and endpoints using semantic knowledge graphs, metadata management, and even machine learning. This helps data management teams to cluster related datasets and also weave new data sources into the data ecosystems. So, it helps eliminate silos across data systems and improve overall data quality.

Data Democracy:  Self-service applications can be built using data fabric architectures. This allows data to be accessed by not only technical teams like data engineers, developers, and data analysts. Cutting down on data bottlenecks. This means more productivity overall, thus becoming an enabler for better and faster decisions.

Improve Data Management: A data fabric can help you manage your data more effectively by providing a single, unified view of all your data. This can help you to identify and track data more easily, and to make better use of your data overall.

Reduce Costs: A data fabric can help you to reduce the costs associated with data management, by allowing you to consolidate your data into a single platform. This can save you time and money.

Better Safeguarding of Data and Compliance: Increasing data access does not have to compromise data security. By putting more safeguards around access controls, it ensures that specific data is only available to certain roles. Using data fabric architectures cuts down on risks associated with data sharing.