Data engineering case-study in digitalized manufacturing

The combination of big data and machine learning appears in the manufacturing context frequently. In a modern factory, data is collected everywhere. It is a challenge for the companies, finding their way to use the produced data. The model's quality is strongly dependent on the quality of the training dataset; the data engineer is responsible for the infrastructure, like providing context and quality input-data for machine learning algorithms. In the discussed case-study, a data pipeline is introduced as a potential solution. It proposes a strategy through the organization, from the shop floor to decision- makers.