Digital transformation and artificial intelligence are significantly reshaping enterprise data landscapes. New data platforms such as data lakes are set up and various self-service solutions are introduced with the goal to systematically store and manage the huge amount of data generated across the value chain and exploit it for competitive advantages.
Metadata management becomes a critical success factor in this endeavor as it constitutes the basis for self-service and governance across the entire data landscape. It fosters data discovery and data analytics in data lakes. It also supports transparency and compliance of data management across analytical and operational data platforms.
While there are many concepts, techniques and tools for metadata management, most focus on sub-aspects, e.g., metadata management with semantic technologies. There is no common understanding of what comprehensive metadata management in an enterprise entails and how it can be implemented. It is the goal of this project to design concepts and techniques for comprehensive metadata management across the entire enterprise data landscape.