Knowledge Management Becomes Business Critical as Knowledge Graphs Improve Decision Making and Efficiency

This webinar is recorded and available on YouTube.

The red arrow finds its optimal path through many impassable options. Strategic planning, business development, search for new markets and opportunities. Risk management, making the right decisions.Historically, knowledge management (KM) was mostly about nurturing controlled vocabularies and taxonomies for the sake of manual document indexing. While nowadays taxonomies often play an important role in various content management (CM) and data management (DM) systems, there are still relatively few enterprises that consider KM an essential business function. 

To remain competitive, enterprises must get insights and make decisions based on knowledge, derived from both structured and unstructured information. The information behind these insights is increasingly more complex, integrating disparate internal and external sources. Leading organizations now rely on big teams of data scientists. Their recommendations count on the richness and the quality of the information being analyzed. To get a real advantage, an enterprise should get the right features and signals on time, without massive efforts for ad hoc data cleaning, transformation and normalization. Today’s data warehouses and enterprise search systems (referred to by Gartner as “Insight engines”) cope well with structural transformations and indexing, but cannot achieve alignment of the meaning of the information on all the necessary levels: terminology, data schema and individual entities.

What you will learn

In this webinar, Atanas Kiryakov, CEO of Ontotext and Joe Hilger, COO of Enterprise Knowledge will present how knowledge graphs (KG) address these challenges by making concepts and entities first-class citizens that have rich descriptions with unambiguous formal semantics. Linking in a network a critical mass of domain knowledge brings context. The kind of cognitive context and awareness that allows human experts to understand and interpret information in a correct and intelligent manner.

Having such a comprehensive conceptual model allows KG-centric systems to:

• Fuse data from diverse sources in an efficient, sustainable and accurate manner;
• Combine proprietary knowledge artifacts with 3rd party models and data;
• Automatically tag documents and extract data with unmatched correctness;
• Mix and match hybrid analytic techniques in order to get more relevant results in less time, spot patterns and derive competitive insights.

What Joe and Atanas have in common is over 20 years of experience in helping the most knowledge-intensive enterprises across multiple sectors (government, life sciences, publishing, financial services, industry, etc.) climb up the Data-Information-Knowledge-Wisdom pyramid. Atanas will present a mindmap of KG applications and explain how Ontotext Platform supports the different stakeholders. Joe will elaborate EK’s methodology for KG-centric solutions, including how their hybrid analysis approach, combining user- and technology-driven research, allows them to iteratively capture relationships between the application, business, information and technology layers. He will present a palette of use cases across Enterprise Architectures, Natural Language Search, Recommendation systems, Data Portals and Catalogues.

Who is this webinar for:

• Knowledge Managers, Content Managers, and IT professionals
• Consultants, Solution Architects, and Knowledge Engineers

Expected duration:

• 45 minutes presentation
• 15 minutes Q&A session