Content related to How a Knowledge Graph Supports AI: Technical Considerations
Data Fabric Solution Vendor Evaluation for a Multinational Pharmaceutical Company
The Challenge A major multinational pharmaceutical company faced challenges with having information stored across collections of structured and unstructured documents that are difficult to index and search. To address this, the company sought a data fabric solution that extracts relevant … Continue reading
Unlocking Dark Data: AI Strategies for Enhanced Data Governance
Wondering how to safeguard your data and mitigate accidental leaks? Dive into our infographic to discover EK’s approach, which incorporates data crawling, pattern matching, and the strategic use of AI and ML models, designed to secure your data and prevent … Continue reading
What Every CEO Needs to Know About Semantic Layers
Recently, we at Enterprise Knowledge have been talking a lot about Semantic Layers, defining what they are, and even what they aren’t. We’ve detailed the various technical components and the business value of each, presented logical diagrams, and identified many … Continue reading
Breaking Down Enterprise AI, Part I: Insight Track
2023 was an incredibly exciting year for artificial intelligence. Several technology trends – distributed computing, transformer models, and large repositories of data – converged to produce powerful generative AI products like ChatGPT and Midjourney. These products have helped generate excitement … Continue reading
What Isn’t a Semantic Layer?
Semantic layers allow organizations to embed context with their organizational data in a way that is systematically interoperable and intuitive to business users. With developments in data and AI, there is a compelling need (and opportunity) for semantic layer development, … Continue reading
What is a Large Language Model (LLM)?
In late November of 2022, artificial intelligence (AI) research and development company OpenAI released ChatGPT, an AI chatbot powered by a Large Language Model (LLM). In the following year, the world witnessed a meteoric rise in the usage of … Continue reading
How to Prepare Content for AI
Artificial Intelligence (AI) enables organizations to leverage and manage their content in exciting new ways, from chatbots and content summarization to auto-tagging and personalization. Most organizations have a copious amount of content and are looking to use AI to improve … Continue reading
Graph Machine Learning Recommender POC for Public Safety Agency
The Challenge A government agency responsible for regulating and enforcing occupational safety sought to build a content recommender proof-of-concept (POC) that leverages semantic technologies to model the relevant workplace safety domains. The agency aimed to optimize project planning and construction … Continue reading
The Top 5 Reasons for a Semantic Layer
Implementing Semantic Layers has become a critical strategic plan for many of our most advanced data clients. A Semantic Layer connects all organizational knowledge assets, including content items (files, videos, media, etc.) via a well defined and standardized semantic framework. … Continue reading
Measuring the Value of your Semantic Layer: KPIs for Taxonomies, Ontologies, and Knowledge Graphs
Utilizing semantic applications in your business, such as an enterprise taxonomy, ontology, or knowledge graph, can increase efficiency, reduce cognitive load, and improve cohesion across the enterprise, among other benefits. While these benefits are extremely valuable they can be difficult … Continue reading