data

In order to cope with growing customer requirements and the associated increase in complexity, companies are opening up their value chains, reducing their vertical integration and increasingly entering into collaborations. Cross-company data exchange along the supply chain is thus becoming a key component for competitiveness and the realization of customer-specific solutions. For this reason, the European Union has launched the GAIA-X project, which aims to create the next generation of data infrastructure for Europe and its companies. The GAIA-X maturity model offers an approach for classifying companies into different development stages and provides concrete requirements for further development along a predefined development path towards becoming a fully-fledged participant in the federated GAIA-X data infrastructure.

Artificial intelligence has the potential to bring companies and entire industries to a completely new technological level. The prerequisite is data with a high degree of maturity, with which companies can automate complex processes, calculate forecasts or create analyses. With the right data strategy, structuring and achieving the necessary data quality are no longer dreams of the future.

For many years now, it is a widespread goal of knowledge management to employ knowledge as a resource: Projects aim - but often fail - at optimising processes of generating, distributing, and applying knowledge. This can be attributed in many cases to (one of) three causes: - The basic difference between “knowledge” and “data” is misunderstood - The benefit of knowledge management seems to be regarded as inevitable, while it is not defined as a tangible goal - Projects focus on ideal concepts and processes, losing contact with organisational realities We show how to avoid those pitfalls, how to identify the potential of knowledge management and how to realise it.