Why Do You Need a Logical Data Fabric?
Enterprise data is diverse, growing, and distributed across cloud and regional boundaries, as the data management ecosystem is constantly evolving. A logical data fabric is a flexible, reusable, and powerful data management approach that is critical for any digital transformation, data governance, or advanced analytics initiatives. With a logical data fabric, powered by data virtualization, enterprises can integrate, manage, and deliver their distributed data to any user, in real time, regardless of the location and format of the source data.
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A logical data fabric can help organizations to knit together disparate data sources in their broad, hybrid universe of data platforms, just as they can make use of data virtualization to create logical data warehouses that expand users’ reach beyond the limitations of traditional enterprise data warehouses.
Logical Data Fabric and Data Virtualization
A logical data fabric is a composable architecture in that its necessary components, such as the data integration layer, data catalog, AI/ML engine, and semantic layer, can be a combination of different sets of tools. But a tightly integrated platform that offers all the necessary components of a logical data fabric always offers the optimal outcome as opposed to multiple different tools and technologies glued together through complex coding and connectivity options. More importantly, a logical data fabric with data virtualization as the underlying data integration approach avoids the replication of data and is critical in providing real-time, aggregated views of data across hybrid/multi-cloud environments while bringing down costs, accelerating time-to-insight, and helping organizations to establish centralized data privacy, security, and governance.
Make data virtualization a must-have data integration component within the broader data management and integration portfolio to assist with agility, reusability, and cost optimization in data integration design and delivery.