Knowledge graphs and graph technologies are among the fastest-growing segments of the AI market, and are probably the most forward-looking information technologies companies are currently dealing with. With graph technologies a new era of data management begins, in which the roles of business, development, and database engineering have to be rethought. At the same time, graph technologies play a prominent role in so many areas of data management that the overview can quickly be lost.
In this tutorial we will take a closer look at different fields of application of knowledge graphs, which include:
- Data quality management
- Data preparation (e.g. for machine learning applications)
- Data integration
- Text Mining and Advanced Data Analysis
- Enterprise-wide data governance
This tutorial also provides a comprehensive overview of the underlying concepts behind knowledge graphs and graph databases. Use cases and hands-on sessions provide a practice-oriented introduction to the topic, and provide knowledge about concrete methods and pitfalls that can be important for the implementation of knowledge graphs and Semantic AI applications.
Juergen Jakobitsch is an Enterprise Data Architect who has worked for Semantic Web Company as a consultant for over 10 years. He works for Fortune 500 companies to help them developing their own Semantic AI strategy and Enterprise Knowledge Graphs. Juergen is a highly experienced Semantic Web specialist who started his career as a Java software engineer. One of his specialities is to explain sophisticated enterprise data architectures to business architects while translating abstract data models into use cases relevant to the end-users.
Andreas Blumauer is a pioneer in the field of Semantic Web and has been working in the field of semantic technologies since 2001. For the past 15 years, he has been CEO of Semantic Web Company (SWC). At SWC he is responsible for business development and strategic product management of PoolParty Semantic Suite (http://www.poolparty.biz) - a semantic middleware for the development of applications based on Linked Data, Machine Learning and Semantic Web Standards.
Andreas is the editor of the first comprehensive book on the Semantic Web. He is an experienced consultant in information architecture, knowledge management, metadata management, linked data, semantic search, data analysis, text mining and machine learning. He regularly speaks at international conferences on topics ranging from artificial intelligence to knowledge management.
