FlowData takes a massive database and, out of it, generates a virtual one that is much smaller and that contains the essential information
FlowData represents a new paradigm in the treatment of multidimensional databases. There is no need for a priori statistical hypothesis. Data patterns are obtained as they are. The technology has been extensively tested in projects for the aerospace sector. Preliminary tests in data analysis (no aerospace) gave very promising results. The first FlowData application would be for more sophisticate risk engines for credit card fraud detection
FlowData represents a new paradigm in the treatment of multidimensional databases.
FlowData relies on tensor analysis techniques (High Order Singular Value Decomposition and Proper Orthogonal Decomposition) instead of statistical methods. The main advantage is that there is no need to formulate a priori hypothesis regarding the statistical distributions of data. Global patterns are obtained as they are.
FlowData has been preliminarily tested in the problem of bank deposits distribution in the USA as a function of state, county and year. Results are very promising both in terms of size reduction and reconstruction errors
“FlowData generates small virtual databases that replicate the original ones while keeping the essential information”
“Decision making in complex environments is becoming more and more sophisticated; FlowData facilitates this sophistication”
“FlowData is the ideal partner for multinational corporations that continuously make decisions in complex environments. Next steps will aim to penetrate markets other than finance and banking that involve simultaneous data analysis and decision making”
Flow Data Contact
Ángel Velázquez
e: angel.velazquez@upm.es
UPM Contact
Área de Innovación, Comercialización y Creación de Empresas
Centro de Apoyo a la Innovación Tecnológica – UPM
e: innovacion.tecnologica@upm.es