More Industries...
The most significant barrier to realizing the value of combined data from high variety sources such as mobile devices, social networks, and sensors is the need to integrate data to perform analysis. Data integration for predictive modeling is complex, expensive, and challenged to respond to data dynamics. In addition, communicating and assembling large integrated datasets for machine learning is increasingly in tension with proprietary and security considerations. What is needed is a cost-effective means of quantifying the value of information and integrating diverse analytics into a unified model, without ever integrating the data.
These problems are prevalent across industries and the value propositions for Collaborative Analytics apply broadly.
Please see future updates to this list.