Whitepaper

Data virtualization, which is a core component of the logical data fabric, can play an important role in supporting the need to access, manage, and analyze data across disparate platforms for traditional reporting and BI — as well as modern use cases such as machine learning and artificial intelligence, integrated analytics for automated decision making, and analysis combining traditional data at rest with real-time streaming data sources.

This checklist describes six important capabilities of the logical data fabric to deal with modern data management and analytics efforts that will include multiple platforms, new data types and sources, and more advanced analytics. These capabilities include data analyst enablement across the emerging hybrid multicloud data landscape and encompass techniques for seamless data integration across multicloud platforms, how augmented intelligence facilitates data awareness and seamless accessibility while maintaining high operational performance, and how boosting performance through optimizations reduces the delays associated with data latency.

Additionally, the checklist discusses how to support data science initiatives through data discovery as well as analysis that combines data at rest and data in motion. Finally, the checklist reinforces the value of data awareness and the use of a data fabric as an enterprise data catalog.