Self-Governing Data Security: Making Data Autonomous

Trust and access are the two biggest impediments to leveraging big data to solve important problems and enable organizations to peer around corners to prepare for future challenges. As hyperconnectivity drives exponential growth in data volume, variety and velocity, organizations will need to form data supply chains to enable accurate automated decision making. Current paradigms in centralized top-down data security and governance, entity-centric perimeter security protocol, and methods for data analytics and machine learning will not scale as currently architected in a hyperconnected world. Security must be made to follow data at the cell-level in order to make it autonomous for use in widespread and ad-hoc data supply chains. Lack of trust inhibits access to needed granular data sets from external sources. With good reason. Myngl.IO software solves this “Trusted Access” problem, allowing data from internal and external sources to be commingled, fused and combinatorially analyzed in real time to solve important problems. We developed a Self-Governing Data Security mechanism that prevents data misuse and provides data “Publishers” 100% control over how and by whom each data element in each data set is used. This allows new areas of analytic exploration, machine learning and artificial intelligence that require richer, more diverse combined data sets.