Explorative Data Analysis

Sophisticated explorative data analysis or data mining techniques are required for an efficient evaluation of the huge multivariate data sets produced in modern laboratories or extracted from contemporary data bases. The search for hidden signals and interesting structures involves a spectrum of strategies ranging from unsupervised automated approaches to fully predefined classical statistical procedures.

In our philosophy a knowledge based approach which combines advanced multivariate techniques with the insight of experts from the respective field is preferable. 
A thoughtful application of modern techniques like cluster analysis, classification and regression trees and intelligent visualisation is as important as a continuous interaction with the interested customer. To this aim a typical project of StatSciConsult is built from different steps.


The benefit of such an explorative data project is high: With moderate costs the customer gets valuable information from expensive data. Technically the results are evidences or supported hypotheses which could guide the path for independent studies or further investigations.