The Thales approach is structured around three closely interconnected themes: Big data (data management and storage), Big Analytics (processing, enrichment and value creation) and Visual Analytics (exploitation and interactive visualisation of datasets using parallelisable and/or linearisable analysis algorithms to ensure exhaustivity).
Through the CeNTAI laboratory, which is the focal point for the Group's Big data activities, Thales is developing both supervised learning algorithms (regression, decision trees, SVM, standard neural networks, expectation maximization, classification, etc.) and unsupervised learning algorithms (auto-encoders, clustering, copula theory, Markov chains, self-learning networks, etc.).
A generic platform has been set up has been set up at the CeNTAI lab, with a Big data architecture based on NoSQL and Elasticsearch to store and access large volumes of heterogeneous, dynamic data from information systems either in batch mode or real time, and Big Analytics and Visual Analytics algorithms primarily dedicated to data fusion, intelligent queries, type analysis, community detection, anomaly and weak-signal detection and investigation, predictive analysis and decision support.