Content related to Understanding the Role of Knowledge Intelligence in the CRISP-DM Framework: A Guide for Data Science Projects
Semantic Layer Symposium 2025: Knowledge Graphs Panel — The Rising Star of the Knowledge Management Toolkit
In October of this year, Enterprise Knowledge held our annual Semantic Layer Symposium (SLS) in Copenhagen, Denmark, bringing together industry thought leaders, data experts, and practitioners to explore the transformative potential, and reflect on the successful implementation, of semantic layers. … Continue reading
Semantic Layer Symposium 2025: Using Semantics to Reduce Hallucinations and Overcome Agentic Limits – Neuro-Symbolic AI and the Promise of Agentic AI
In October of this year, Enterprise Knowledge held our annual Semantic Layer Symposium (SLS) in Copenhagen, Denmark, bringing together industry thought leaders, data experts, and practitioners to explore the transformative potential, and reflect on the successful implementation, of semantic layers. … Continue reading
How Taxonomies and Ontologies Enable Explainable AI
Taxonomy and ontology models are essential to unlocking the value of knowledge assets. They provide the structure needed to connect fragmented information across an organization, enabling explainable AI. As part of a broader Knowledge Intelligence (KI) strategy, these models help … Continue reading
How to Leverage LLMs for Auto-tagging & Content Enrichment
When working with organizations on key data and knowledge management initiatives, we’ve often noticed that a roadblock is the lack of quality (relevant, meaningful, or up-to-date) existing content an organization has. Stakeholders may be excited to get started with advanced … Continue reading
Knowledge Cast – Michal Bachman, CEO of GraphAware
Enterprise Knowledge COO Joe Hilger speaks with Michal Bachman, CEO at GraphAware. GraphAware provides technology and expertise for mission-critical graph analytics, and its graph-powered intelligence analysis platform — Hume — is used by democratic government agencies (law enforcement, intelligence, cybersecurity, … Continue reading
Navigating the Retirement Cliff: Challenges and Strategies for Knowledge Capture and Succession Planning
As organizations prepare for workforce retirements, knowledge management should be a key element of any effective succession planning strategy, ensuring a culture of ongoing learning and stability. This piece explores the challenges organizations face in capturing and transferring critical knowledge, … Continue reading
Defining Governance and Operating Models for AI Readiness of Knowledge Assets
Artificial intelligence (AI) solutions continue to capture both the attention and the budgets of many organizations. As we have previously explained, a critical factor to the success of your organization’s AI initiatives is the readiness of your content, data, and … Continue reading
Semantic Layer Strategy: The Core Components You Need for Successfully Implementing a Semantic Layer
Today’s organizations are flooded with opportunities to apply AI and advanced data experiences, but many struggle with where to focus first. Leaders are asking questions like: “Which AI use cases will bring the most value? How can we connect siloed … Continue reading
Capture as You Work: Embedding Knowledge Capture in Daily Work
Knowledge capture is most effective when it is embedded as part of your daily work, not an occasional task. But we know that it is easier said than done. Enterprise Knowledge regularly hears from our clients that: “We don’t have … Continue reading
How to Ensure Your Content is AI Ready
In 1996, Bill Gates declared “Content is King” because of its importance (and revenue generating potential) on the World Wide Web. Nearly 30 years later, content remains king, particularly when leveraged as a vital input for Enterprise AI. Having AI-ready … Continue reading