Earlier this year, the Semantic Layer Symposium in Munich brought together industry leaders, data scientists, and Knowledge Management (KM) experts to explore cutting-edge developments in data integration and AI-driven insights. This groundbreaking event fostered lively discussions on the future of semantic layers, knowledge management, and the role of AI in transforming data practices. We’re excited to release these discussions for viewing, offering insights from top voices in the field and paving the way for innovative applications of semantic layer technology.
In his presentation, Dr. Norbert Gergely discusses his work with Zeiss in implementing a semantic layer to unify data across its diverse business units. Zeiss, a 200-year-old company with divisions in areas like semiconductor technology, medical devices, and consumer optics, faces unique challenges in managing complex data from numerous sources and product types. Norbert explains how Zeiss’s semantic layer and knowledge graph infrastructure have been developed to address these challenges by creating interoperable, structured data systems that enhance data accessibility, especially for teams like customer service and R&D.
Norbert outlines specific use cases, such as a service platform for microscopy devices, where a knowledge graph and AI-supported backend help field engineers troubleshoot equipment with minimal downtime. Another example in the MedTech division involves integrating diverse data types, including patient records and imaging, to improve diagnostics and treatment tracking. He also highlights the importance of continuous business feedback and iterative development to ensure the solution evolves with user needs.
Looking ahead, Norbert envisions expanding Zeiss’s semantic framework to support digital twins and improved data interoperability across divisions. His advice to organizations considering semantic implementations includes starting small with focused, value-driven use cases and iteratively scaling up. This strategy not only mitigates risk but also builds stakeholder trust, demonstrating the measurable impact of semantic solutions on business operations.