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.
This is achieved through the uniform anonymization of personal identifying information (PII) and the creation of secure execution environments for the querying of shared data. In doing so, no PII is ever passed from one entity to another or at risk of being lost.
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