Content related to How Semantic Layers Support Product Search and Discovery
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
AI & Taxonomy: the Good and the Bad
The recent popularity of new machine learning (ML) and artificial intelligence (AI) applications has disrupted a great deal of traditional data and knowledge management understanding and tooling. At EK, we have worked with a number of clients who have questions–how … 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
Enterprise AI Architecture Series: How to Extract Knowledge from Unstructured Content (Part 2)
Our CEO, Zach Wahl, recently noted in his annual KM trends blog for 2025 that Knowledge Management (KM) and Artificial Intelligence (AI) are really two sides of the same coin, detailing this idea further in his seminal blog introducing the … Continue reading
Knowledge Cast – Ahren Lehnert at Nike
Enterprise Knowledge CEO Zach Wahl speaks with Ahren Lehnert, Principal Taxonomist at Nike. In this conversation, Zach and Ahren discuss the future of taxonomy and artificial intelligence (AI), emphasizing both the augmentation of traditional roles and growth to include new … Continue reading
Metadata Within the Semantic Layer
As a standardized framework for connecting organizational assets, a Semantic Layer captures organizational knowledge and domain meaning to support connecting and coordinating assets across systems and repositories. Metadata, as one component of a Semantic Layer approach, is foundational. Whether you … Continue reading
Why Graph Implementations Fail (Early Signs & Successes)
Organizations continue to invest heavily in efforts to unify institutional knowledge and data from multiple sources. This typically involves copying data between systems or consolidating it into a new physical location such as data lakes, warehouses, and data marts. With … Continue reading
Enhancing Retail Performance with Semantic Layer As an Enabler for Data and Analytics Teams
In the fast-paced retail sector, organizations need to be able to quickly view store performance analytics in order to make crucial decisions. A leading global retail chain faced significant delays of up to 5-6 weeks when attempting to retrieve essential store performance metrics and create reports for executive leadership. This bottleneck was largely due to … Continue reading