StatsCube applications make up a complete data-life-cyclesupporting framework, including data validation, data enrichment and efficient analytical tools.
This application offers facilities for efficiently and effectively executing a statistical data processing algorithms. The application relies on the distributed and elastic computing capacities offered by the underlying infrastructure. It currently embeds many different algorithms ranging from Anomalies Detection, Classification, Clustering, Simulation, Training, Bayesian Methods, Trends, and many more. These algorithms are executed on a distributed infrastructure by completely hiding the complexity of such an execution while ensuring robustness, throughput, fault-tolerance, and privacy.