Big Data

Economy, enterprises and employees are sustainably affected by digital transformation. The new opportunities of education and training to evaluate learner behavior digitally are of particular interest. Learning analytics can be used for specific optimization of learning forms and content for the benefit of learners and of the training company.

The implementation of industry 4.0 concepts requires a new understanding of data processing and analysis. Data Science integrates approaches of mathematical modelling and performant implementation to analyse data of specific application areas. Within this first article, the basics of Data Science are presented and perspectives for a data-driven production and logistics are discussed. Within a second article in a following edition, the process steps for structured data analysis will be explained and illustrated by means of application examples.

The volatile world urges companies to react more agile to fast changes. Monitoring is a major building block for corporate agility. A lack of understanding of causal interrelations between a multitude of volatility drivers demands a new monitoring approach. Big data is presented as an adequate tool and its agility support is discussed from a data and analytics point of view. Conclusively, guidelines for developing a monitoring system are discussed.