Content related to Ivanov and Midkiff to Speak at the Cognitive Computing Summit 2018 in Boston, MA
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
Enterprise AI Architecture Series: How to Build a Knowledge Intelligence Architecture (Part 1)
Since the launch of ChatGPT over two years ago, we have observed that our clients are increasingly drawn to the promise of AI. They also recognize that the large language models (LLMs), trained on public data sets, may not effectively … Continue reading
Enterprise AI Meets Access and Entitlement Challenges: A Framework for Securing Content and Data for AI
In today’s digital landscape, organizations face a critical challenge: how to leverage the power of Artificial Intelligence (AI) while ensuring their knowledge assets remain secure and accessible to the right people at the right time. As enterprise AI systems become … Continue reading
Data Management and Architecture Trends for 2025
Today, many organizational leaders are focused on AI readiness, and as the AI transformation is accelerating, so are the trends that define how businesses look for, store, secure, and leverage data and content. The future of enterprise data management and … 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
A Semantic Layer to Enable Risk Management at a Multinational Bank
Enterprise Knowledge is working with a multinational bank to enable their risk-assessing processes by using semantics and connected data. Heavily regulated financial services firms require comprehensive and complex risk management. This requires employees to thoroughly account for risk and report it in detail to regulators. Continue reading