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Graph Analytics in the Semantic Layer: Architectural Framework for Knowledge Intelligence

Introduction As enterprises accelerate AI adoption, the semantic layer has become essential for unifying siloed data and delivering actionable, contextualized insights. Graph analytics plays a pivotal role within this architecture, serving as the analytical engine that reveals patterns and relationships … Continue reading

Beyond Traditional Machine Learning: Unlocking the Power of Graph Machine Learning

Traditional machine learning (ML) workflows have proven effective in a wide variety of use cases, from image classification to fraud detection. However, traditional ML leaves relationships between data points to be inferred by the model, which can limit its ability … Continue reading

The Role of Taxonomy in Labeled Property Graphs (LPGs) & Graph Analytics

Taxonomies play a critical role in deriving meaningful insights from data by providing structured classifications that help organize complex information. While their use is well-established in frameworks like the Resource Description Framework (RDF), their integration with Labeled Property Graphs (LPGs) … Continue reading

How to Implement a Semantic Layer: A Proven Operating Model

As organizations invest in enterprise AI and knowledge intelligence, the semantic layer serves as a critical foundation for providing a consistent, contextual framework that connects data assets across multiple sources to enable shared understanding, interoperability, and more intelligent use of … Continue reading

Knowledge Portals: Manifesting A Single View Of Truth For Your Organization

Guillermo Galdamez, Principal Knowledge Management Consultant, and Benjamin Cross, Project Manager, presented “Knowledge Portals: Manifesting A Single View Of Truth For Your Organization” at the APQC 2025 Process & Knowledge Management Conference on April 9th, 2025. Galdamez and Cross delivered … Continue reading

Enhancing Taxonomy Management Through Knowledge Intelligence

In today’s data-driven world, managing taxonomies has become increasingly complex, requiring a balance between precision and usability. The Knowledge Intelligence (KI) framework – a strategic integration of human expertise, AI capabilities, and organizational knowledge assets – offers a transformative approach … Continue reading