Product development is required to ensure a high level of product quality at maximum cost efficiency. Simulation and test runs produce valuable data, the added value of which is their appropriate linkage.

The data undergo harmonization and standardization treatment as part of the pre-processing. Different methods are employed to analyze them: aggregation, compression, transformation, calculation of characteristic values and even complex machine-learning algorithms. Vast amounts of unstructured data are usually stored in an object store.

A sensible measure to exploit the data's full potential is a modular data analytics toolchain that can be integrated into the corporate landscape.