Content related to Mastering the Dark Data Challenge: Harnessing AI for Enhanced Data Governance and Quality
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
Getting Control of Your Content: AI Solutions to Streamline and Optimize Your Digital Assets
Paula Land, Principal Consultant for Content Strategy and Operations and Elliott Risch, Semantic AI Consultant, presented a LavaCon pre-conference webinar on the topic of AI-assisted content analysis titled Getting Control of Your Content: AI Solutions to Streamline and Optimize Your … Continue reading
AI-Ready Content Accelerator
AI solutions are only as good as the content that powers them. When content lacks the necessary quality, structure, and enhancement, AI tools will fail to appropriately understand it, leading to a high risk of “hallucinations,” as well as distrust … Continue reading
How Data Becomes Dark
Are you navigating through the complexities of managing your enterprise’s unstructured data? This infographic shows the journey from data creation to its eventual transformation into ‘dark data’—data that remains underutilized and potentially exposes organizations to risks. We break down the … Continue reading
A Semantic Layer Approach to Enterprise Knowledge Management and Information Findability
Within an organization or enterprise, multiple knowledge organization systems tend to be siloed and used for different purposes in different systems (the website, the intranet, technical documentation publishing, the product catalog, customer support articles, training materials, etc.). If this disparate … Continue reading
The Metadata Knowledge Graph
Modern data landscapes are characterized by immense volumes of diverse, disparate, and dynamic data sources, leaving many organizations struggling to effectively manage and derive value from their data assets. To address these challenges, a metadata knowledge graph serves as a … Continue reading
A Tale of Two Semantic Layers
In the rapidly evolving landscape of information and data management, the term Semantic Layer is increasingly utilized to describe two different types of ‘layers’ in the modern data stack. The first Semantic Layer is focused on enabling centralized analytics within … Continue reading
Building a Semantic Layer of your Data Platform
Enterprise Knowledge’s Joe Hilger, COO, and Sara Nash, Principal Consultant, presented “Building a Semantic Layer of your Data Platform” at Data Summit Workshop on May 7th, 2024 in Boston, Massachusetts. This presentation delved into the importance of the semantic layer … Continue reading
The Role of AI in the Semantic Layer
Two significant recent trends in knowledge management, artificial intelligence (AI) and the semantic layer, are reshaping the way organizations interact with their data and leverage it to derive actionable insights. Taking advantage of the interplay between AI and the semantic … Continue reading
Enterprise Knowledge Graphs: The Importance of Semantics
Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “Enterprise Knowledge Graphs: The Importance of Semantics” on May 9, 2024, at the annual Data Summit in Boston. In her presentation, Hedden describes the components of an enterprise knowledge graph and provides … Continue reading