Content related to Integrating Search and Knowledge Graphs Series Part 1: Displaying Relationships
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
Extracting Knowledge from Documents: Enabling Semantic Search for Pharmaceutical Research and Development
The Challenge A major pharmaceutical research and development company faced difficulty creating regulatory reports and files based on years of drug experimentation data. Their regulatory intelligence teams and drug development chemists spent dozens of hours searching through hundreds of thousands … 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
Multimodal Graph RAG (mmGraphRAG): Incorporating Vision in Search and Analytics
David Hughes, Principal Data & AI Solution Architect at Enterprise Knowledge, presented “Unleashing the Power of Multimodal GraphRAG: Integrating Image Features for Deeper Insights” at Data Day Texas 2025 in Austin, TX on Saturday, January 25th. In this presentation, David … Continue reading
A Guide to Selecting the Right Auto-Tagging Approach
Auto-tagging processes automate the manual labor of applying relevant keyword tags to data and content, enhancing accessibility and improving the organization of large datasets. Whether you’re trying to improve how quickly you find data or embarking on a content cleanup … Continue reading