Designing Metadata Management in Complex Enterprise Data Landscapes (MetaMan)

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.

Continue reading →

Designing a comprehensive Data Lake Architecture (DLArchitecture)

Initiatives like Industry 4.0 generate large amounts of heterogeneous data that need to be stored and managed. It is not always clear what benefits this data will later bring to the company. As a result, it is usually not possible to decide at the time of data collection what value the data will have. To avoid losing any potentially important information, all data are stored in their raw format in an enterprise-wide data lake. The goal of this project was to define a framework for an implementable data lake architecture.

Continue reading →