SEAMLESS DATA CONSOLIDATION

 

The most of the experiments are designed to study a problem from a variety of approaches and identify novel relationships among them.

 

This requires capturing, storing and combining information coming from different equipment and software packages.

 

AutoDiscovery saves you a lot of time every day by performing an automatic consolidation process which joins the rows and columns of the imported data files into a single data table. 

 

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Once done, the data variables can be arranged into "data sources" to facilitate the analysis and exploration of the results.

 

The example above shows how 3 data files including information related to learning, neural structure and anxiety essays are consolidated in a single data table containing variables from the 3 different data sources. The Discovery Map and Hypo Booster tool facilitate exploring the results for each of these data sources and their crossed relationships.