Knowledge Graphs: Only the Essentials

Recorded Webinar

Knowledge Graphs (KGs) help to give answers to questions. They reveal hidden connections, and they bring data structures closer to the human-like way of processing information. So close that they can be even visualized without the need to run any specific transformation or interpretation steps upfront. KGs help to make Smart Data from Big Data.

Based on ‘Four Generic Problems addressed by Semantic Knowledge Graphs,’ Andreas Blumauer, CEO of the Semantic Web Company, and Yanko Ivanov, Senior Consultant at Enterprise Knowledge, talked about the benefits organizations gain from this approach of ‘smart data management.’ Watch the on-demand webinar to learn more about the four generic problems, which are:

Loosely connected data
Too simplistic, disconnected data models
Data models don’t keep pace with market dynamics
Too abstract data models

If you would like to stay up to date with more information about Knowledge Graphs, be sure to join our Knowledge Graphs and Semantic AI LinkedIn Group to discuss with the Knowledge Graph Society and various industry experts!

What is a Knowledge Graph?

“It’s all about things, not strings: A Knowledge Graph represents a knowledge domain. It connects things of different types in a systematic way. Knowledge graphs encode knowledge arranged in a network of nodes and links rather than tables of rows and columns. By that, people and machines can benefit from a dynamically growing semantic network of facts about things and can use it for data integration, knowledge discovery, and in-depth analyses.”

Andreas Blumauer

CEO and Founder, Semantic Web Company