Big Test Data or Big Measurement Data refers to large volumes of measurement data that play a role above all during the development phase (e.g., of vehicles, airplanes or components for aerospace missions). For the optimization of the driving behavior, of the powertrain or during crash tests, a constantly increasing range of different measurands is collected in real-time. This is also true for the development of consumer goods, for optimizing the maintenance of special-purpose machines or conducting research for the maritime industry. The acquired data is then prepared, visualized and analyzed to obtain information and - ideally - knowledge about cause-and-effect relationships.
What opportunities are offered by Big Test Data?
As with the processing of personal data, a great deal of unused potential remains in the analysis of large volumes of measurement data: using suitable software, for example, it is possible to test hypotheses and acquire knowledge, e.g., by means of pattern recognition through suitable algorithms. Measurement data differs significantly from other types of data in that it is usually only meaningful in combination with physical units and time index.
How can one capitalize on Big Test Data?
In addition to the sensor systems for producing the data and the hardware for the data acquisition, it is above all special software that makes the difference – on three levels:
- Availability: the produced volumes of measurement data must be managed and organized efficiently
- Operationalization: data processing, visualization, and analysis of the data to obtain useful information
- Data mining: comparative pattern recognition to obtain fundamental knowledge about relationships – including over time and with test series
