Knowledge Cast by Enterprise Knowledge KM Trends - Semantic Layer
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Feb 8, 2024 Explore the potential of the Semantic Layer in knowledge management, including its impact on knowledge graphs, taxonomies, and content management. Discover the challenges of fragmented information and the need for customized solutions. Learn about the importance of incorporating unstructured data and taxonomies in knowledge graphs, as well as the benefits of automated tagging and taxonomy for course content. Explore the competitive advantage of data productization and unique training sets. Finally, delve into the potential of semantic layers for breaking down organizational barriers in knowledge management.
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Semantic Layer Definition
- A semantic layer contextualizes data, connecting it with metadata regardless of storage location.
- It shifts focus from data itself to its meaning, using taxonomies, ontologies, and knowledge graphs.
Why Semantic Layers Now?
- Generative AI's hunger for data drives the need for semantic layers to contextualize information.
- This helps prevent hallucinations and ensures the AI understands the organization's context.
Product Definition Challenge
- Zach Wahl shares an experience where defining "product" took three months of a six-month taxonomy project.
- This highlights the business challenge of aligning definitions, not just a technical one.