Data Analysis using Statistical Analysis and Forecasting, Data Mining Techniques and Econometrics.
Contemporary data analysis and modeling does not involve segregation among knowledge fields. For example Data Mining combines classic statistical methods, artificial intelligence and the modern field of knowledge discovery in databases (KDD). The newest methods of regression and classification are nowadays the Support Vector Machines that combine Neural Networks and Optimization. Benchmarking is based on techniques using statistical methods as well as Operational Research.
The above prove that implementing a demanding data analysis or modeling project requires an inter-scientific approach.
Some examples of such applications are:
• Forecasting (sales, demand etc).
• Advanced techniques in customer segmentation.
• Metrics and evaluation model development – credit risk management and market risk.
• Business units’ modern evaluation methods.
• Management Information Systems (MIS) for decision making and problem solving in production planning, fleet management etc.
• Statistical simulation methods for process optimization and reengineering.
Our innovative Data Analysis services include a wide range of knowledge and aggregate experience. In addition to this our strategic partnerships and cooperation with academic and research institutions ensure the successful implementation of the projects and the consistent knowledge dissemination.