Content related to Industry Panel: Different Applications of a Semantic Layer — Takeaways Blog
Cutting Through the Noise: An Introduction to RDF & LPG Graphs
Graph is good. From capturing business understanding to support standardization and data analytics to informing more accurate LLM results through Graph-RAG, knowledge graphs are an important component of how modern businesses translate data and content into actionable knowledge and information. … Continue reading
Fostering a Knowledge-Sharing Mindset: How to Get People to Share What They Know
Knowledge is one of an organization’s most valuable assets, but it’s only useful when shared. Organizations become more innovative, efficient, and resilient when employees actively exchange insights, best practices, and lessons learned. However, knowledge sharing doesn’t always happen naturally—it requires the right culture, incentives, and support. Continue reading
Unlocking Knowledge Intelligence from Unstructured Data
Introduction Organizations generate, source, and consume vast amounts of unstructured data every day, including emails, reports, research documents, technical documentation, marketing materials, learning content and customer interactions. However, this wealth of information often remains hidden and siloed, making it challenging … Continue reading
Enterprise AI Architecture Series: How to Inject Business Context into Structured Data using a Semantic Layer (Part 3)
Introduction AI has attracted significant attention in recent years, prompting me to explore enterprise AI architectures through a multi-part blog series this year. Part 1 of this series introduced the key technical components required for implementing an enterprise AI architecture. … Continue reading
What is Semantics and Why Does it Matter?
This white paper will unpack what semantics is, and walk through the benefits of a semantic approach to your organization’s data across search, usability, and standardization. As a knowledge and information management consultancy, EK works closely with clients to help … Continue reading
What are the Different Types of Graphs? The Most Common Misconceptions and Understanding Their Applications
Over 80% of enterprise data remains unstructured, and with the rise of artificial intelligence (AI), traditional relational databases are becoming less effective at capturing the richness of organizational knowledge assets, institutional knowledge, and interconnected data. In modern enterprise data solutions, … Continue reading
How a Semantic Layer Transforms Engineering Research Industry Challenges
To drive future innovation, research organizations increasingly seek to develop advanced platforms that enhance the findability and connectivity of their knowledge, data, and content–empowering more efficient and impactful R&D efforts. However, many face challenges due to decentralized information systems, where … Continue reading
The Minimum Requirements To Consider Something a Semantic Layer
Semantic Layers are an important design framework for connecting information across an organization in preparation for Enterprise AI and Knowledge Intelligence. But with every new technology and framework, interest in utilizing the technological advance outpaces experience in effective implementation. As … Continue reading
The Resource Description Framework (RDF)
Simply defined, a knowledge graph is a network of entities, their attributes, and how they’re related to one another. While these networks can be captured and stored in a variety of formats, most implementations leverage a graph based tool or … Continue reading
Nurturing Knowledge – A Journey in Building a KM Program from Scratch: A Case Study
Today, non-profit organizations face the challenge of optimizing knowledge management to maximize resources and support decision-making. During this presentation “Nurturing Knowledge: A Journey in Building a KM Program from Scratch”, Jess DeMay (Enterprise Knowledge) and Jennifer Anna (WWF) shared a … Continue reading