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Establishing a Scalable Knowledge Management Strategy and Solution Framework for a Leading Automotive Manufacturing Company: A Case Study

One of the top global leaders in automotive manufacturing faced significant challenges in managing and accessing critical knowledge across its diverse teams. The company engaged Enterprise Knowledge (EK) to conduct a Knowledge Management (KM) Strategy and solution implementation project plan after the failure of multiple KM initiatives. The engagement’s long-term goal is to establish a shared Knowledge Management System (KMS) to streamline access to crucial information, better leverage experts’ institutional knowledge and experience, and decrease new employees’ time to proficiency. Continue reading

Content Mastermind (Taylor’s Version): What Taylor Swift Can Teach Us About The Benefits of Repurposing Content

In January of 2025, Taylor Swift charted #1 on Billboard, breaking a record for most Number 1s on the Top Album Sales list with a new version of an almost six-year-old album. The 2025 repressing of Lover (Live from Paris) … Continue reading

Semantic Layer Maturity Framework Series: Taxonomy

Taxonomy is foundational to the Semantic Layer. A taxonomy establishes the essential semantic building blocks upon which everything else is built, starting by standardizing naming conventions and ensuring consistent terminology. From there, taxonomy concepts are enriched with additional context, such … Continue reading

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