Trusted Data sharing can be severely hampered by issues that “slow down” data, such as lack of interoperability, incompatible data collection and querying protocols, and low-speed ETL processes. This element of data sharing is often overlooked as, technically, the data is still shared. But the hidden cost is how much value has been lost in transit.
Data operations require considerable upfront investment and ongoing running costs before the benefits of data analysis and sharing can be seen. Therefore, making a case for consistent ROI is a challenge for most data functions, especially when competing for resources with other areas of the organization.
The solution to all of these issues, and many others, is the use of virtualized data platforms to handle data sharing. Data virtualization creates an interoperable data layer that draws together only the data needed for specific queries wherever it is located. It simultaneously improves data security by performing data operations inside secure containers, giving data administrators the ability to deploy fine-grained access controls over all data sharing at intertrust.com.