Data is raw, unanalyzed facts. It can be structured or unstructured. Using various processing techniques, it can be converted into information.
Data mining refers to the automatic evaluation of large amounts of data. The aim is to discover correlations or regularities.
Digitization influences almost all areas of daily life. Documents that used to be available only in analogue form (e.g. books or films) can now be read or downloaded in digital form. This also applies to all other forms of data. As a result, this data can be collected and analyzed.
The term servitization describes a process in which the manufacturing industry evolves in the direction of services. This means that the company no longer solely offers products, but also other associated services. One example is the maintenance of machines. A connection with digitization can be established if machine data is used to predict the wear of certain parts as accurately as possible.
Socio-economic research focuses on both the economy and society. Economic developments can change society (e.g. the smartphone). In the same way, social change can influence the economy (e.g. the desire for a better work-life balance).
Value creation is the economic performance of a company. The value chain refers to all necessary processes (e.g. supply – production – delivery). In the value creation network, these steps are no longer linear, but move along different channels that influence each other. For example, this gives customers more influence over the product to be manufactured.
The term work 4.0 covers questions about the future of work. The aim is to find out how we intend to shape and organize the future of the working world, which has changed as a result of digitization. This includes considerations on technical innovations and working-time models as well as on the opportunities and risks associated with them.