Knowledge Cast – Ben Clinch, Chief Data Officer & Partner at Ortecha – Semantic Layer Symposium Series
Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Ben Clinch, Chief Data Officer and Partner at Ortecha and Regional Lead Trainer for the EDM Council (EMEA/India). He is a sought-after public speaker and thought leader in … Continue reading
When Should You Use An AI Agent? Part One: Understanding the Components and Organizational Foundations for AI Readiness
It’s been recognized for far too long that organizations spend as much as 30-40% of their time searching for or recreating information. Now, imagine a dedicated analyst who doesn’t just look for or analyze data for you but also roams … Continue reading
Knowledge Cast – Dawn Brushammar, Independent Knowledge Management Consultant & Programme Chair of KMWorld Europe – Semantic Layer Symposium Series
Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Dawn Brushammar, currently an independent KM consultant, advisor, and frequent contributor at industry events. She has spent her 25+ year career connecting people to relevant knowledge and information. … Continue reading
Knowledge Cast – Paco Nathan, Principal DevRel Engineer at Senzing – Semantic Layer Symposium Series
Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Paco Nathan, Developer Relations (DevRel) Leader for the Entity Resolved Knowledge Graph Practice at Senzing. He is a computer scientist with over 40 years of tech industry experience … Continue reading
The Evolution of Knowledge Management & Organizational Roles: Integrating KM, Data Management, and Enterprise AI through a Semantic Layer
On June 23, 2025, at the Knowledge Summit Dublin, Lulit Tesfaye and Jess DeMay presented “The Evolution of Knowledge Management (KM) & Organizational Roles: Integrating KM, Data Management, and Enterprise AI through a Semantic Layer.” The session examined how KM … Continue reading
Top Semantic Layer Use Cases and Applications (with Real World Case Studies)
Today, most enterprises are managing multiple content and data systems or repositories, often with overlapping capabilities such as content authoring, document management, or data management (typically averaging three or more). This leads to fragmentation and data silos, creating significant inefficiencies. … Continue reading
What are the Different Types of Graphs? The Most Common Misconceptions and Understanding Their Applications
Over 80% of enterprise data remains unstructured, and with the rise of artificial intelligence (AI), traditional relational databases are becoming less effective at capturing the richness of organizational knowledge assets, institutional knowledge, and interconnected data. In modern enterprise data solutions, … Continue reading
Data Management and Architecture Trends for 2025
Today, many organizational leaders are focused on AI readiness, and as the AI transformation is accelerating, so are the trends that define how businesses look for, store, secure, and leverage data and content. The future of enterprise data management and … Continue reading
Why Graph Implementations Fail (Early Signs & Successes)
Organizations continue to invest heavily in efforts to unify institutional knowledge and data from multiple sources. This typically involves copying data between systems or consolidating it into a new physical location such as data lakes, warehouses, and data marts. With … Continue reading
How to Inject Organizational Knowledge in AI: 3 Proven Strategies to Achieve Knowledge Intelligence
Generative AI (GenAI) has made Artificial Intelligence (AI) more accessible to the business, specifically by empowering organizations to leverage large language models (LLMs) for a wide range of applications. From enhancing customer support to automating content creation and operational processes, … Continue reading