Data analysis is a process of gathering, modeling, and transforming data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains. Our expertise in the field of data analysis covers the following subjects.
- Sensor Signal Analysis. Data analysis tools are incorporated into most measurement systems. SINTEF uses a long range of methods to analyse and model sensor signals, from deterministic simulation methods, via combined and fully empirical statistical methods, to advanced non-linear multivariate methods with fuzzy decisions.
- Sensor and data fusion. Often one sensor or one measurement principle can not capture all the information needed to make a desired conclusion. The idea with sensor and data fusion is to use inputs from complementary information sources that when combined, can be used to draw conclusions that can not be obtained from any of the sources alone.
- Multivariate Analysis. Many processes, both technical and social, depend on several known, and unknown, variables and have complex interactions between them. Multivariable methods are a collection of statistical techniques which pursuit knowledge of a process by analyzing more than one statistical variable simultaneously.