View from the top by Jan Aasman, CEO
Gartner recently identified Knowledge Graphs as a key new technology in both their Hype Cycle for Artificial Intelligence and Hype Cycle for Emerging Technologies. Using AI to create “Enterprise Knowledge” and link it across the Enterprise to create a “Knowledge Graph” is a key differentiator for companies in an increasingly competitive landscape. Semantic Graph databases, such as AllegroGraph, provide the core technology environment to enrich and contextualize the understanding of data. The ability to rapidly integrate new knowledge is the crux of the Knowledge Graph and depends entirely on Semantic Graph technologies.
AllegroGraph is a multi-model (Graph and Document) database technology that enables businesses to extract sophisticated decision insights and predictive analytics from highly complex, distributed data. AllegroGraph employs graph technologies that process data with contextual and conceptual intelligence and significantly enhances the document database model with its native support for JSON and JSON-LD. Knowledge Graphs can leverage JSON-LD to swiftly integrate with web-based applications. Organizations can therefore link specific information in their internal Knowledge Graphs (e.g., pertaining to customers or products) to web applications for timely action such as recommendations.
Knowledge Graph Development
Franz provides a variety of services as part of its Knowledge Graph solution, from architectural consulting and technical seminars to training. If you really want to develop your corporate Knowledge Graph and address complex AI problems, you need a data system that goes beyond just data. You have to create a system that can link to anything outside your own predefined parameters—and that can learn from previous experiences. That is where a Semantic Graph Database, like AllegroGraph, comes into the picture.